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Association of Obesity With Survival Outcomes in Patients With Cancer

Fausto Petrelli, Alessio Cortellini, Alice Indini and 13 more

JAMA Network Open · 2021 · Meta-analysis

doi:10.1101/2020.04.28.20082800

Abstract

Question. Is obesity associated with better prognosis in patients with cancer?

Findings. This meta-analysis of 203 studies with more than 6.3 million participants found that obesity was associated with increased overall and cancer-specific mortality, especially among patients with breast, colon, and uterine cancer. In contrast, patients with obesity and renal cell carcinoma, lung cancer, or melanoma had better survival than patients without obesity.

Meaning. These findings suggest that survival outcomes are poor among patients with obesity and cancer, except in lung cancer and melanoma.

Importance. Obesity, defined as a body mass index (BMI) greater than 30, is associated with a significant increase in the risk of many cancers and in overall mortality. However, various studies have suggested that patients with cancer and no obesity (ie, BMI 20-25) have worse outcomes than patients with obesity.

Objective. To assess the association between obesity and outcomes after a diagnosis of cancer.

Data Sources. PubMed, the Cochrane Library, and EMBASE were searched from inception to January 2020.

Study Selection. Studies reporting prognosis of patients with obesity using standard BMI categories and cancer were included. Studies that used nonstandard BMI categories, that were limited to children, or that were limited to patients with hematological malignant neoplasms were excluded. Screening was performed independently by multiple reviewers. Among 1892 retrieved studies, 203 (17%) met inclusion criteria for initial evaluation.

Data Extraction and Synthesis. The Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines were reporting guideline was followed. Data were extracted by multiple independent reviewers. Risk of death, cancer-specific mortality, and recurrence were pooled to provide an adjusted hazard ratio (HR) with a 95% CI. A random-effects model was used for the retrospective nature of studies.

Main Outcomes and Measures. The primary outcome of the study was overall survival (OS) in patients with cancer, with and without obesity. Secondary end points were cancer-specific survival (CSS) and progression-free survival (PFS) or disease-free survival (DFS). The risk of events was reported as HRs with 95% CIs, with an HR greater than 1 associated with a worse outcome among patients with obesity vs those without.

Results. A total of 203 studies with 6 320 365 participants evaluated the association of OS, CSS, and/or PFS or DFS with obesity in patients with cancer. Overall, obesity was associated with a reduced OS (HR, 1.14; 95% CI, 1.09-1.19; P <.001) and CSS (HR, 1.17; 95% CI, 1.12-1.23; P <.001). Patients were also at increased risk of recurrence (HR, 1.13; 95% CI, 1.07-1.19; P <.001). Conversely, patients with obesity and lung cancer, renal cell carcinoma, or melanoma had better survival outcomes compared with patients without obesity and the same cancer (lung: HR, 0.86; 95% CI, 0.76-0.98; P =.02; renal cell: HR, 0.74; 95% CI, 0.53-0.89; P =.02; melanoma: HR, 0.74; 95% CI, 0.57-0.96; P <.001).

Conclusions and Relevance. In this study, obesity was associated with greater mortality overall in patients with cancer. However, patients with obesity and lung cancer, renal cell carcinoma, and melanoma had a lower risk of death than patients with the same cancers without obesity. Weight-reducing strategies may represent effective measures for reducing mortality in these patients.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 17, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

Obesity, defined as a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) greater than 30, is a chronic disease with increasing prevalence around the world, largely contributing to important health issues in most countries. Alongside body fat, which is a general risk factor for serious illness (eg, metabolic syndrome), greater cardiometabolic risk has also been associated with the localization of excess fat in the visceral adipose tissue and ectopic deposits. Several large epidemiologic studies have evaluated the association between obesity and mortality. In particular, a meta-analysis of 230 cohort studies including more than 30 million individuals found that both obesity and overweight were associated with an increased risk of all-cause mortality. Despite the evidence that excess mortality increases with increasing BMI, some studies have reached the conclusion that elevated BMI may improve survival in patients with cardiovascular disease, a phenomenon called the obesity paradox.

Increased BMI is also associated with an increased risk of multiple cancer types. In addition, obesity and overweight may increase cancer mortality. During last decades, we have observed a more rapid increase in obesity among adult cancer survivors compared with the general population. The mechanisms contributing to higher cancer incidence and mortality may include alterations in sex hormone metabolism, insulin and insulin-like growth factor levels, and adipokine pathways.,

Various studies have suggested that patients with cancer and a normal BMI (ie, 20-25) have worse outcomes than patients with obesity. This phenomenon (ie, the obesity paradox) in cancer is not well understood and presents controversial explanations.,, Three different meta-analyses have led to different results, in particular in lung and renal cell carcinomas.,, In lung cancer, obesity is favorably associated with long-term survival of surgical patients. Moreover, in renal cell carcinoma, an inconsistent association of BMI with cancer-specific survival (CSS) was found. Conversely, breast, ovarian, and colorectal cancer are invariably associated with increased mortality in patients with obesity.,, The main explanations for these observations include the general poor health status of patients with very low BMI. Additionally, weight loss may be associated with frailty and other risk factors (eg, smoking). In cancer, obesity is also associated with increased efficacy of programmed cell death 1 and programmed cell death ligand 1 (PD-1/PD-L1) blockade in both tumor-bearing mice and patients. This updated systematic review and meta-analysis was conducted to evaluate the prognosis of patients with cancer who have obesity vs those without obesity.

Search Strategy and Inclusion Criteria

We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline, A systematic search was conducted of EMBASE, PubMed, and the Cochrane Library for articles published from database inception until September 30, 2020. The following search terms were used: ((carcinoma or cancer or sarcoma or melanoma or (“Neoplasms”[MESH])) AND (obese OR obesity OR 30 kg/m2 OR “body mass index”) AND (hazard ratio) AND survival AND (multivariate OR cox or multivariable). The reference lists of identified articles were then manually searched to identify potentially relevant omitted citations. Articles that were not published in English were not included.

Retrospective and observational studies (ie, cohort, case-control) or prospective trials were selected when they reported the association of obesity, defined as a BMI of at least 30, with the risk of death (ie, overall survival [OS]), CSS, disease-free survival (DFS), or progression-free survival (PFS) in patients with cancer compared with counterparts without obesity (ie, BMI <30). We placed no restrictions on study setting, size, race, or country. Included studies were limited to those reporting hazard ratios (HRs) and their corresponding 95% CIs. Studies were restricted to adult patients with solid tumors. Hematologic malignant neoplasms were excluded. Short-term survival studies (eg, postsurgical mortality) were also excluded. Baseline-only BMI evaluation was considered (eg, BMI captured at cancer diagnosis in early-stage cancers or at metastatic disease in advanced-stage cancers).

The most up-to-date versions of full-text publications were included. Study selection was performed in 2 stages. First, titles and abstracts were screened; then, selected full-text articles were included according to the eligibility criteria. If pooled analyses of more than 1 study were evaluated for inclusion, the included articles were manually evaluated for duplicate inclusion compared with the other eligible articles. Screening was performed independently by 10 authors (M.G., G.T., A.G., A. Indini, A.C., O.N., V.R., A. Iaculli, L.D., M.S.), and conflicts were handled by consensus with a senior author (F.P.).

Data Collection and Quality Assessment

Data were collected independently by using a predesigned spreadsheet (Excel version 2007 [Microsoft Corp]). Collected data items included authors, year of publication, study setting and design, median follow-up, treatments received, outcomes, and type of analysis. The primary outcome was OS; secondary end points were CSS and PFS or DFS. Along with data extraction, 1 author (F.P.) assessed study quality according to a modified Newcastle Ottawa Scale (NOS; range 1-9, with 1-3 indicating low quality, 4-6 indicating moderate quality, and 7-9 indicating high quality).

Statistical Analysis

First, pooled HRs with 95% CIs were estimated using random-effects meta-analysis with the generic inverse-variance method for studies that provided fully adjusted HRs. Inconsistency across studies was measured with the I2 method. Cutoff values of 25%, 50%, and 75% indicated low, moderate, and high heterogeneity, respectively. When I2 was larger than 50%, a random-effects model was primarily used because of the retrospective nature of included studies. To examine heterogeneity, we performed exploratory analyses of predefined subgroups based on type of disease, type of study, duration of follow-up, and race. Additionally, to address potential bias and verify our results, we performed sensitivity analyses using a leave-one-out method and the trim-and-fill method. These methods explore whether there are potential dominant studies that may have driven the results. Finally, to investigate the risk of publication bias, we applied the Egger test and visually inspected the funnel plots (ie, the Begg test). If the distribution of studies is symmetrical, the meta-analysis most likely does not have problems with publication bias. All statistical tests were 2-sided using a significance level of P <.05. All analyses were carried out using Comprehensive Meta-Analysis software version 3.3.070.

Results

Our literature search yielded 1892 articles, of which 203 (17%) met the inclusion criteria for our overall systematic review of the association of obesity with cancer outcomes (Figure). Most excluded studies did not use the prespecified cutoff value for obesity (ie, BMI values different from 30 in 437 studies) or used a continuous cutoff for risk of death (eg, 1 unit-increase in BMI in 235 studies). Of the 203 articles, 170 (84%) were eligible for inclusion in the systematic review of the association of obesity with OS, 109 (54%) for association with CSS, and 79 (39%) for association with DFS or PFS. Descriptive data for studies included in our meta-analysis are listed in Table 1.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Overall, the included studies included a total of 6 320 365 patients. Sample sizes ranged from 41 to 1 096 492 patients, with a median of 1543. Most studies were retrospective in nature (132 studies [63%]); the minority were prospective cohort or observational studies (63 studies [31%]) or pooled analyses or randomized trials (8 studies [4%]). Multivariable analysis was performed in 197 studies. Overall, 136 studies (63%) reported a significant association of obesity with the outcome in at least 1 end point. The mean NOS score was 7 (median, 7.5; range, 5-9), indicating that the overall quality of articles was good.

OS and Obesity in Patients With Cancer

A total of 170 studies reported data on OS. Because the heterogeneity test showed a high level of heterogeneity (I2 = 79.7%; P <.001) among studies, a random-effects model was used for the analysis. OS among patients with obesity was significantly worse than that among patients without obesity (HR, 1.14; 95% CI, 1.09-1.19; P <.001) (eFigure 1 in the Supplement). The association of obesity with outcomes was independent by other main cancer prognostic factors, including stage (100%), sex (85%), age (100%), race (80%), smoking status (83%), and other comorbidities according to multivariable analysis.

CSS and Obesity in Patients With Cancer

Similarly, obesity was associated with reduced CSS in 109 studies (HR, 1.17; 95% CI, 1.12-1.23; P <.001) (eFigure 2 in the Supplement). Heterogeneity was high (I2 = 73.9%; P <.001), so a random-effects model was used.

DFS or PFS and Obesity in Patients With Cancer

In 79 studies, obesity was associated with worse DFS or PFS compared with not having obesity (HR, 1.13; 95% CI, 1.07-1.19; P <.001) (eFigure 3 in the Supplement). Heterogeneity was high (I2 = 73.7%; P <.001), so a random-effects model was used.

Subgroup Analysis

A subgroup analysis for OS was performed according to type of disease (Table 2, Table 3, and Table 4). Patients with breast, colorectal, or uterine cancers and obesity had higher overall mortality than those without obesity (breast: HR, 1.26; 95% CI, 1.2-1.33; P <.001; colorectal: HR, 1.22; 95% CI, 1.14-1.31; P <.001; HR, 1.20; 95% CI, 1.04-1.38; P =.01). Patients with obesity and lung cancer, renal cell carcinoma, or melanoma had better survival outcomes compared with patients without obesity and the same cancer (lung: HR, 0.86; 95% CI, 0.76-0.98; P =.02; renal cell: HR, 0.74; 95% CI, 0.53-0.89; P =.02; melanoma: HR, 0.74; 95% CI, 0.57-0.96; P <.001). CSS was decreased in patients with obesity and breast, colorectal, prostate, and pancreatic cancers (breast: 1.23; 95% CI, 1.15-1.32; P <.001; colorectal: HR, 1.24; 95% CI, 1.16-1.32; P <.001; prostate: HR, 1.26; 95% CI, 1.08-1.47; P =.01; pancreatic: HR, 1.28; 95% CI, 1.05-1.57; P =.01). DFS was decreased in patients with obesity and breast, colorectal, prostate, and gastroesophageal cancers (breast: HR, 1.14; 95% CI, 1.1-1.19; P <.001; colorectal: HR, 1.15; 95% CI, 1.01-1.3; P =.01; prostate: HR, 1.29; 95% CI, 1.07-1.56; P <.001; gastroesophageal: HR, 1.62; 95% CI, 1.13-2.32; P <.001). Additional subgroup analyses included type of study (retrospective: HR, 1.07; 95% CI, 1.07-1.18; P <.001; prospective: HR, 1.14; 95% CI, 1.05-1.23; P <.001), duration of follow up (>10 years: HR, 1.16; 95% CI, 0.86-1.58; P =.08; <10 years: HR, 1.23; 95% CI, 0.84-1.63; P =.09), race (non-Asian race: HR, 1.22; 95% CI, 0.86-1.66, P =.06; Asian race: HR, 1.22; 95% CI, 0.74-1.72; P =.09), and stage of disease (early: HR, 1.20; 95% CI, 0.99-1.25; P =.07; advanced: HR, 1.2; 95% CI, 1.12-1.28; P =.01). Regression analysis according to NOS score was not significant.

Publication Bias

A funnel plot was used to assess publication bias in the studies evaluating OS in patients with and without obesity. No publication bias was detected by funnel plot inspection (Begg test). Egger test was instead significant (eFigure 4 in the Supplement). According to the trim-and-fill method, 18 studies were placed to the left of the mean, and according the random-effect model, the final result for OS was similar (HR, 1.08; 95% CI, 1.03-1.13). After the leave-one-out procedure, HRs for OS ranged from 1.14 to 1.15.

Discussion

This meta-analysis found that overall mortality was increased in patients with obesity and breast, colorectal, or uterine cancers. Cancer mortality was increased in breast, colorectal, prostate, and pancreatic cancers. Finally, the relapse rate was increased in breast, colorectal, prostate and gastroesophageal cancers. The obesity paradox, which describes improved cancer and all-cause mortality rates among patients with obesity, was observed in lung cancer and in melanoma; however, these data derive from only 12 studies. We used a categorical BMI definition of obesity (ie, BMI ≥30), because a more standardized definition would permit the comparison and synthesis of studies better than other categories (eg, continuous measures or unit of BMI increase).

The magnitude of effect size was similar for both OS and CSS in breast, colorectal, and lung cancer. This means that obesity may affect both the natural history of cancer and noncancer-related deaths.

Various factors are potentially associated with increased cancer mortality in some malignant neoplasms. Hormonal factors, reduced physical activity, more lethal or aggressive disease behavior, metabolic syndromes, and potential undertreatment in patients with obesity are possible reasons. It is well known that postmenopausal women with higher BMI have an increased risk of breast cancer because of higher estrogen levels resulting from the peripheral conversion of estrogen precursors (from adipose tissue) to estrogen. In these patients, weight loss and exercise may reduce cancer risk by lowering exposure to breast cancer biomarkers. In colorectal cancer, prediagnosis BMI was associated with increased all-cause, cardiovascular, and colorectal cancer–specific mortality. The reason for this association is not presently understood, although insulin, insulin-like growth factors, their binding proteins, chronic inflammation, oxidative stress, and impaired immune surveillance have been supposed to be causative factors. In pancreatic cancer, higher prediagnostic BMI was associated with more advanced stage at diagnosis, with 72.5% of patients with obesity presenting with metastatic disease vs 59.4% of patients with reference-range BMI (P =.02) in 2 large prospective cohort studies. Lastly, in prostate cancer, obesity may be a consequence of androgen deprivation therapy but seems also associated with more aggressive disease (ie, Gleason score ≥7) or more advanced disease at diagnosis.

Our results showed that patients with obesity and lung cancer had significantly prolonged CSS and OS compared with patients without obesity. When considering these findings, we must take into account that 9 of 11 evaluated studies included patients with advanced and/or metastatic disease. Cancer cachexia mechanisms are not completely defined, but research has shown that the systemic inflammatory status induced either by the tumor or host response is a key moment in the development of cachexia. Lung cancers are indeed known to be aggressive, and patients with advanced disease usually have poorer performance statuses and experience significant weight loss at the time of diagnosis, which underlies a systemic inflammatory response. In our studies, obesity was positively associated with OS, independent of smoking status, in patients with lung cancer. Interestingly, a post hoc pooled analysis of randomized prospective trials comparing a PD-L1 checkpoint inhibitor (atezolizumab) with docetaxel in patients with advanced non–small cell lung cancer (NSCLC), revealed that the OS benefit for patients with obesity vs those with reference-range BMI was restricted to patients who received immunotherapy; no association was found in the group receiving docetaxel. Another study also explored the role of baseline BMI and BMI variation during treatment in a cohort of patients with advanced NSCLC and PD-L1 expression of at least 50% who received first-line pembrolizumab (a PD-1 checkpoint inhibitor) and in a control cohort of patients with NSCLC receiving first-line standard chemotherapy, confirming that the survival benefit for patients with obesity was restricted to those receiving immunotherapy.

Similar findings have been described in patients with melanoma receiving immunotherapy, and a survival benefit for patients with obesity was reported in the single study included in our meta-analysis. However, despite some evidence showing that patients with obesity and melanoma who were receiving immune-checkpoint inhibitors achieved better outcomes,, the association is currently questioned, given that opposite results have been reported in a multicenter study.

Interestingly, patients with obesity and renal cell carcinoma also had a significantly longer OS compared with the patients without obesity. It has been hypothesized that the perinephric white adipose tissue acts as a reservoir of activated immune cells, with increased characteristics of hypoxia, infiltration of T helper type 1 cells, regulatory T cells, dendritic cells, and type 1 macrophages. However, only 1 of 6 studies included patients who were receiving immunotherapy.,

Intriguingly, we found that the association between obesity and better clinical outcomes was confirmed for those malignant neoplasms in which immune checkpoint inhibitors have first (and strongly) proved to be effective; however, studies involving patients receiving immune checkpoint inhibitors are poorly represented in this meta-analysis. Such results might be an epiphenomenon; however, we speculate that white adipose tissue could be considered an immune organ, which somehow plays a role in the antitumor immune response. It has been observed that the adipocyte-derived hormone leptin could alter T cell function, resulting in improved response to anti–PD-1 therapy. Moreover, another preclinical study reported that white adipose tissue acts as a reservoir for a peculiar population of memory T cells, which elicit some effective responses in the case of antigenic re-exposure during infections (and why not in case of exposure to cancer-specific antigens?). Finally, considering that immune checkpoint inhibitors exert their action within the tumor microenvironment, modulating the interactions between the tumor and the host, it has been proposed that systemic metabolic conditions, including high blood cholesterol, obesity, hyperglycemia and diabetes, atherosclerosis, and hypertension, may represent the epiphenomena of an inflamed patient. Such a patient might be characterized by an enrichment of cytokines and pro-inflammatory mediators (both in the innate and adaptive compartments) and by a condition of T cell exhaustion, with defective cellular-mediated mechanisms. Nevertheless, in these patients, immune checkpoint blockade might be more effective in reversing this immunological anergy both at the tumor and at the systemic levels.

Patients with obesity are also at increased risk of reduced physical activity. Various studies highlighted this concept. Physical activity decreases over time in patients with obesity., In particular, physical activity is strictly associated with breast cancer and colorectal cancer mortality., Therefore physical activity (or inactivity) should be a major target of obesity prevention and treatment in particular for patients with cancer. Type 2 diabetes is strongly associated with obesity in the metabolic syndrome. More than 80% of cases of type 2 diabetes can be attributed to obesity, which may also account for many diabetes-related deaths. The association between BMI and cause-specific mortality was also illustrated in the Prospective Studies Collaboration analysis. In the upper BMI range (ie, 25 to 50), each 5-unit increase in BMI was associated with a significant increase in mortality from coronary heart disease, stroke, diabetes, chronic kidney disease, and many cancers. In the same analysis, individuals with BMI less than 22.5 had higher mortality compared with individuals with a BMI of 22.5 to 25. The excess mortality was predominantly associated with smoking-related diseases (ie, respiratory disease and cancer). However, there are no clear recommendations about dosing of chemotherapy in patients with obesity, so caution is recommended for high-risk regimens. The hypothesis that a reduced dose according to ideal body weight may lead to a worse outcome cannot be confirmed by prospective studies but may be considered a potential reason for the observed results in some settings (eg, breast cancer). In a pooled analysis of toxic effects in patients with and without obesity, rates of toxic effects were similar or lower in patients with obesity.

Limitations

This study has several limitations. First, we combined data for patients with obesity and compared their prognosis with patients with different weights (ie, normal weight or normal weight and overweight). Second, accurate measures of potentially self-reported weight and height are always a challenge in observational studies. The evaluation often takes place before diagnosis, but in some studies the timing of the obesity diagnosis was not described. Patients with obesity have a generally poor prognosis in terms of overall mortality and noncancer mortality, so it seems obvious that their prognosis would be worse than patients without obesity. However, almost all studies provided a multivariate analysis according to main prognostic factor for oncological outcome so that obesity remains generally an independent prognostic factor in patients with cancer. The outcome was almost never adjusted for private medical insurance, but obesity can increase costs for cancer treatment and complications. Therefore, patients with a lower socioeconomic status may have had reduced access to medical facilities (ie, access to anticancer treatments), rehabilitation, or follow-up intensity and therefore had inferior outcomes. Duration of follow-up, treatments received, and countries were heterogeneous even if subgroup analyses did not explain results with these different variables. Furthermore, this meta-analysis compared mortality between patients belonging to a fixed category of obesity (ie, BMI >30), and thus, we are not able to provide an effect size per unit increment.

Conclusions

In this study, the results supported the notion that obesity is a competing risk factor for overall and cancer specific mortality as well as recurrence in various cancers treated with curative intent or for metastatic disease, except for lung cancer and melanoma, in which obesity was associated with reduced mortality (obesity paradox). These results suggest that oncologists should increase their efforts to manage patients in multidisciplinary teams for care and cure of both cancer and obesity. Improving lifestyle factors (eg, physical activity, caloric intake, care and prevention of cardiovascular complications), more intensive follow-ups of cancer in patients with obesity, and adequate dose of medical therapies are all proven measures that may improve prognosis for patients with cancer and obesity.

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    Arce-Salinas C, Aguilar-Ponce JL, Villarreal-Garza C,. Overweight and obesity as poor prognostic factors in locally advanced breast cancer patients. Breast Cancer Res Treat. 2014;146(1):183-188

    Not in our library10.1007/s10549-014-2977-8

  32. 32.

    Beasley JM, Kwan ML, Chen WY,. Meeting the physical activity guidelines and survival after breast cancer: findings from the after breast cancer pooling project. Breast Cancer Res Treat. 2012;131(2):637-643

    Not in our library10.1007/s10549-011-1770-1

  33. 33.

    Blair CK, Wiggins CL, Nibbe AM,. Obesity and survival among a cohort of breast cancer patients is partially mediated by tumor characteristics. NPJ Breast Cancer. 2019;5(1):33

    Not in our library10.1038/s41523-019-0128-4

  34. 34.

    Braithwaite D, Satariano WA, Sternfeld B,. Long-term prognostic role of functional limitations among women with breast cancer. J Natl Cancer Inst. 2010;102(19):1468-1477

    Not in our library10.1093/jnci/djq344

  35. 35.

    Buono G, Crispo A, Giuliano M,. Combined effect of obesity and diabetes on early breast cancer outcome: a prospective observational study. Oncotarget. 2017;8(70):115709-115717

    Not in our library10.18632/oncotarget.22977

  36. 36.

    Caan BJ, Kwan ML. Pre-diagnosis body mass index, post-diagnosis weight change and prognosis among women with early stage breast cancer. Cancers Causes Control. 2008;19(10):1319-1328

    Not in our library10.1007/s10552-008-9203-0

  37. 37.

    Cecchini RS, Swain SM, Costantino JP,. Body mass index at diagnosis and breast cancer survival prognosis in clinical trial populations from NRG oncology/NSABP B-30, B-31, B-34, and B-38. Cancer Epidemiol Biomarkers Prev. 2016;25(1):51-59

    Not in our library10.1158/1055-9965.epi-15-0334-t

  38. 38.

    Chang S, Alderfer JR, Asmar L, Buzdar AU. Inflammatory breast cancer survival: the role of obesity and menopausal status at diagnosis. Breast Cancer Res Treat. 2000;64(2):157-163

    Not in our library10.1023/a:1006489100283

  39. 39.

    Chen X, Lu W, Zheng W,. Obesity and weight change in relation to breast cancer survival. Breast Cancer Res Treat. 2010;122(3):823-833

    Not in our library10.1007/s10549-009-0708-3

  40. 40.

    Chung IY, Lee JW, Lee JS,. Interaction between body mass index and hormone-receptor status as a prognostic factor in lymph-node-positive breast cancer. PLoS One. 2017;12(3):e0170311

    Not in our library10.1371/journal.pone.0170311

  41. 41.

    Cleveland RJ, North KE, Stevens J, Teitelbaum SL, Neugut AI, Gammon MD. The association of diabetes with breast cancer incidence and mortality in the Long Island Breast Cancer Study Project. Cancer Causes Control. 2012;23(7):1193-1203

    Not in our library10.1007/s10552-012-9989-7

  42. 42.

    Connor AE, Visvanathan K, Baumgartner KB,. Ethnic differences in the relationships between diabetes, early age adiposity and mortality among breast cancer survivors: the Breast Cancer Health Disparities Study. Breast Cancer Res Treat. 2016;157(1):167-178

    Not in our library10.1007/s10549-016-3810-3

  43. 43.

    Conroy SM, Maskarinec G, Wilkens LR, White KK, Henderson BE, Kolonel LN. Obesity and breast cancer survival in ethnically diverse postmenopausal women: the Multiethnic Cohort Study. Breast Cancer Res Treat. 2011;129(2):565-574

    Not in our library10.1007/s10549-011-1468-4

  44. 44.

    Copson ER, Cutress RI, Maishman T,; POSH Study Steering Group. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26(1):101-112

    Not in our library10.1093/annonc/mdu509

  45. 45.

    Crozier JA, Moreno-Aspitia A, Ballman KV, Dueck AC, Pockaj BA, Perez EA. Effect of body mass index on tumor characteristics and disease-free survival in patients from the HER2-positive adjuvant trastuzumab trial N9831. Cancer. 2013;119(13):2447-2454

    Not in our library10.1002/cncr.28051

  46. 46.

    Dal Maso L, Zucchetto A, Talamini R,; Prospective Analysis of Case-control studies on Environmental factors and health (PACE) study group. Effect of obesity and other lifestyle factors on mortality in women with breast cancer. Int J Cancer. 2008;123(9):2188-2194

    Not in our library10.1002/ijc.23747

  47. 47.

    Dignam JJ, Wieand K, Johnson KA, Fisher B, Xu L, Mamounas EP. Obesity, tamoxifen use, and outcomes in women with estrogen receptor-positive early-stage breast cancer. J Natl Cancer Inst. 2003;95(19):1467-1476

    Not in our library10.1093/jnci/djg060

  48. 48.

    Dignam JJ, Wieand K, Johnson KA,. Effects of obesity and race on prognosis in lymph node-negative, estrogen receptor-negative breast cancer. Breast Cancer Res Treat. 2006;97(3):245-254

    Not in our library10.1007/s10549-005-9118-3

  49. 49.
    Obesity and breast cancer outcomes in chemotherapy patients in New Zealand – a population-based cohort study · 2018
    Not checked
  50. 50.

    Emaus A, Veierød MB, Tretli S,. Metabolic profile, physical activity, and mortality in breast cancer patients. Breast Cancer Res Treat. 2010;121(3):651-660

    Not in our library10.1007/s10549-009-0603-y

  51. 51.

    Feliciano EMC, Kroenke CH, Meyerhardt JA,. Association of systemic inflammation and sarcopenia with survival in nonmetastatic colorectal cancer: results from the C SCANS Study. JAMA Oncol. 2017;3(12):e172319

    Not in our library10.1001/jamaoncol.2017.2319

  52. 52.

    Goodwin PJ, Ennis M, Pritchard KI,. Insulin- and obesity-related variables in early-stage breast cancer: correlations and time course of prognostic associations. J Clin Oncol. 2012;30(2):164-171

    Not in our library10.1200/jco.2011.36.2723

  53. 53.

    He X, Esteva FJ, Ensor J, Hortobagyi GN, Lee MH, Yeung SC. Metformin and thiazolidinediones are associated with improved breast cancer-specific survival of diabetic women with HER2+ breast cancer. Ann Oncol. 2012;23(7):1771-1780

    Not in our library10.1093/annonc/mdr534

  54. 54.

    Hellmann SS, Thygesen LC, Tolstrup JS, Grønbaek M. Modifiable risk factors and survival in women diagnosed with primary breast cancer: results from a prospective cohort study. Eur J Cancer Prev. 2010;19(5):366-373

    Not in our library10.1097/cej.0b013e32833b4828

  55. 55.

    His M, Fagherazzi G, Mesrine S, Boutron-Ruault MC, Clavel-Chapelon F, Dossus L. Prediagnostic body size and breast cancer survival in the E3N cohort study. Int J Cancer. 2016;139(5):1053-1064

    Not in our library10.1002/ijc.30158

  56. 56.

    Jeon YW, Kang SH, Park MH, Lim W, Cho SH, Suh YJ. Relationship between body mass index and the expression of hormone receptors or human epidermal growth factor receptor 2 with respect to breast cancer survival. BMC Cancer. 2015;15(1):865

    Not in our library10.1186/s12885-015-1879-4

  57. 57.

    Jiralerspong S, Kim ES, Dong W, Feng L, Hortobagyi GN, Giordano SH. Obesity, diabetes, and survival outcomes in a large cohort of early-stage breast cancer patients. Ann Oncol. 2013;24(10):2506-2514

    Not in our library10.1093/annonc/mdt224

  58. 58.

    Kawai M, Tomotaki A, Miyata H,. Body mass index and survival after diagnosis of invasive breast cancer: a study based on the Japanese National Clinical Database-Breast Cancer Registry. Cancer Med. 2016;5(6):1328-1340

    Not in our library10.1002/cam4.678

  59. 59.

    Keegan THM, Milne RL, Andrulis IL,. Past recreational physical activity, body size, and all-cause mortality following breast cancer diagnosis: results from the Breast Cancer Family Registry. Breast Cancer Res Treat. 2010;123(2):531-542

    Not in our library10.1007/s10549-010-0774-6

  60. 60.

    Kwan ML, Chen WY, Kroenke CH,. Pre-diagnosis body mass index and survival after breast cancer in the After Breast Cancer Pooling Project. Breast Cancer Res Treat. 2012;132(2):729-739

    Not in our library10.1007/s10549-011-1914-3

  61. 61.

    Kwan ML, John EM, Caan BJ,. Obesity and mortality after breast cancer by race/ethnicity: the California Breast Cancer Survivorship Consortium. Am J Epidemiol. 2014;179(1):95-111

    Not in our library10.1093/aje/kwt233

  62. 62.

    Ladoire S, Dalban C, Roché H,. Effect of obesity on disease-free and overall survival in node-positive breast cancer patients in a large French population: a pooled analysis of two randomised trials. Eur J Cancer. 2014;50(3):506-516

    Not in our library10.1016/j.ejca.2013.11.013

  63. 63.

    Larsen SB, Kroman N, Ibfelt EH, Christensen J, Tjønneland A, Dalton SO. Influence of metabolic indicators, smoking, alcohol and socioeconomic position on mortality after breast cancer. Acta Oncol. 2015;54(5):780-788

    Not in our library10.3109/0284186x.2014.998774

  64. 64.

    Loi S, Milne RL, Friedlander ML,. Obesity and outcomes in premenopausal and postmenopausal breast cancer. Cancer Epidemiol Biomarkers Prev. 2005;14(7):1686-1691

    Not in our library10.1158/1055-9965.epi-05-0042

  65. 65.

    Maskarinec G, Pagano I, Lurie G, Bantum E, Gotay CC, Issell BF. Factors affecting survival among women with breast cancer in Hawaii. J Womens Health (Larchmt). 2011;20(2):231-237

    Not in our library10.1089/jwh.2010.2114

  66. 66.

    McCullough ML, Feigelson HS, Diver WR, Patel AV, Thun MJ, Calle EE. Risk factors for fatal breast cancer in African-American women and White women in a large US prospective cohort. Am J Epidemiol. 2005;162(8):734-742

    Not in our library10.1093/aje/kwi278

  67. 67.

    McCullough LE, Chen J, Cho YH,. DNA methylation modifies the association between obesity and survival after breast cancer diagnosis. Breast Cancer Res Treat. 2016;156(1):183-194

    Not in our library10.1007/s10549-016-3724-0

  68. 68.

    Nichols HB, Trentham-Dietz A, Egan KM,. Body mass index before and after breast cancer diagnosis: associations with all-cause, breast cancer, and cardiovascular disease mortality. Cancer Epidemiol Biomarkers Prev. 2010;18(5):1403-1409

    Not in our library10.1158/1055-9965.epi-08-1094

  69. 69.
    A prospective investigation of oral contraceptive use and breast cancer mortality: findings from the Swedish women’s lifestyle and health cohort · 2019
    Not checked
  70. 70.

    Oh SW, Park CY, Lee ES,. Adipokines, insulin resistance, metabolic syndrome, and breast cancer recurrence: a cohort study. Breast Cancer Res. 2011;13(2):R34

    Not in our library10.1186/bcr2856

  71. 71.

    Oudanonh T, Nabi H, Ennour-Idrissi K,. Progesterone receptor status modifies the association between body mass index and prognosis in women diagnosed with estrogen receptor positive breast cancer. Int J Cancer. 2020;146(10):2736-2745

    Not in our library10.1002/ijc.32621

  72. 72.

    Pajares B, Pollán M, Martín M,. Obesity and survival in operable breast cancer patients treated with adjuvant anthracyclines and taxanes according to pathological subtypes: a pooled analysis. Breast Cancer Res. 2013;15(6):R105

    Not in our library10.1186/bcr3572

  73. 73.

    Pfeiler G, Stöger H, Dubsky P,; ABCSG. Efficacy of tamoxifen ± aminoglutethimide in normal weight and overweight postmenopausal patients with hormone receptor-positive breast cancer: an analysis of 1509 patients of the ABCSG-06 trial. Br J Cancer. 2013;108(7):1408-1414

    Not in our library10.1038/bjc.2013.114

  74. 74.

    Pierce JP, Stefanick ML, Flatt SW,. Greater survival after breast cancer in physically active women with high vegetable-fruit intake regardless of obesity. J Clin Oncol. 2007;25(17):2345-2351

    Not in our library10.1200/jco.2006.08.6819

  75. 75.

    Probst-Hensch NM, Steiner JHB, Schraml P,. IGFBP2 and IGFBP3 protein expressions in human breast cancer: association with hormonal factors and obesity. Clin Cancer Res. 2010;16(3):1025-1032

    Not in our library10.1158/1078-0432.ccr-09-0957

  76. 76.

    Senie RT, Rosen PP, Rhodes P, Lesser ML, Kinne DW. Obesity at diagnosis of breast carcinoma influences duration of disease-free survival. Ann Intern Med. 1992;116(1):26-32

    Not in our library10.7326/0003-4819-116-1-26

  77. 77.

    Sparano JA, Wang M, Zhao F,. Race and hormone receptor-positive breast cancer outcomes in a randomized chemotherapy trial. J Natl Cancer Inst. 2012;104(5):406-414

    Not in our library10.1093/jnci/djr543

  78. 78.

    Sparano JA, Wang M, Zhao F,. Obesity at diagnosis is associated with inferior outcomes in hormone receptor-positive operable breast cancer. Cancer. 2012;118(23):5937-5946

    Not in our library10.1002/cncr.27527

  79. 79.

    Su HI, Sue LY, Flatt SW, Natarajan L, Patterson RE, Pierce JP. Endogenous estradiol is not associated with poor physical health in postmenopausal breast cancer survivors. J Womens Health (Larchmt). 2013;22(12):1043-1048

    Not in our library10.1089/jwh.2013.4375

  80. 80.

    Sun X, Nichols HB, Robinson W, Sherman ME, Olshan AF, Troester MA. Post-diagnosis adiposity and survival among breast cancer patients: influence of breast cancer subtype. Cancer Causes Control. 2015;26(12):1803-1811

    Not in our library10.1007/s10552-015-0673-6

  81. 81.

    Sun L, Zhu Y, Qian Q, Tang L. Body mass index and prognosis of breast cancer: an analysis by menstruation status when breast cancer diagnosis. Medicine (Baltimore). 2018;97(26):e11220

    Not in our library10.1097/md.0000000000011220

  82. 82.

    Tait S, Pacheco JM, Gao F, Bumb C, Ellis MJ, Ma CX. Body mass index, diabetes, and triple-negative breast cancer prognosis. Breast Cancer Res Treat. 2014;146(1):189-197

    Not in our library10.1007/s10549-014-3002-y

  83. 83.

    Warren LEG, Ligibel JA, Chen YH, Truong L, Catalano PJ, Bellon JR. Body mass index and locoregional recurrence in women with early-stage breast cancer. Ann Surg Oncol. 2016;23(12):3870-3879

    Not in our library10.1245/s10434-016-5437-3

  84. 84.

    Widschwendter P, Friedl TWP, Schwentner L,. The influence of obesity on survival in early, high-risk breast cancer: results from the randomized SUCCESS A trial. Breast Cancer Res. 2015;17(1):129

    Not in our library10.1186/s13058-015-0639-3

  85. 85.

    Xiao Y, Zhang S, Hou G, Zhang X, Hao X, Zhang J. Clinical pathological characteristics and prognostic analysis of diabetic women with luminal subtype breast cancer. Tumour Biol. 2014;35(3):2035-2045

    Not in our library10.1007/s13277-013-1270-5

  86. 86.

    Mazzarella L, Disalvatore D, Bagnardi V,. Obesity increases the incidence of distant metastases in oestrogen receptor-negative human epidermal growth factor receptor 2-positive breast cancer patients. Eur J Cancer. 2013;49(17):3588-3597

    Not in our library10.1016/j.ejca.2013.07.016

  87. 87.

    Rosenberg L, Czene K, Hall P. Obesity and poor breast cancer prognosis: an illusion because of hormone replacement therapy? Br J Cancer. 2009;100(9):1486-1491

    Not in our library10.1038/sj.bjc.6605025

  88. 88.

    Ademuyiwa FO, Groman A, O’Connor T, Ambrosone C, Watroba N, Edge SB. Impact of body mass index on clinical outcomes in triple-negative breast cancer. Cancer. 2011;117(18):4132-4140

    Not in our library10.1002/cncr.26019

  89. 89.

    Dawood S, Lei X, Litton JK, Buchholz TA, Hortobagyi GN, Gonzalez-Angulo AM. Impact of body mass index on survival outcome among women with early stage triple-negative breast cancer. Clin Breast Cancer. 2012;12(5):364-372

    Not in our library10.1016/j.clbc.2012.07.013

  90. 90.

    Melhem-Bertrandt A, Chavez-Macgregor M, Lei X,. Beta-blocker use is associated with improved relapse-free survival in patients with triple-negative breast cancer. J Clin Oncol. 2011;29(19):2645-2652

    Not in our library10.1200/jco.2010.33.4441

  91. 91.

    Frumovitz M, Jhingran A, Soliman PT, Klopp AH, Schmeler KM, Eifel PJ. Morbid obesity as an independent risk factor for disease-specific mortality in women with cervical cancer. Obstet Gynecol. 2014;124(6):1098-1104

    Not in our library10.1097/aog.0000000000000558

  92. 92.

    Fedirko V, Romieu I, Aleksandrova K,. Pre-diagnostic anthropometry and survival after colorectal cancer diagnosis in Western European populations. Int J Cancer. 2014;135(8):1949-1960

    Not in our library10.1002/ijc.28841

  93. 93.

    Boyle T, Fritschi L, Platell C, Heyworth J. Lifestyle factors associated with survival after colorectal cancer diagnosis. Br J Cancer. 2013;109(3):814-822

    Not in our library10.1038/bjc.2013.310

  94. 94.

    Campbell PT, Newton CC, Newcomb PA,. Association between body mass index and mortality for colorectal cancer survivors: overall and by tumor molecular phenotype. Cancer Epidemiol Biomarkers Prev. 2015;24(8):1229-1238

    Not in our library10.1158/1055-9965.epi-15-0094

  95. 95.

    Cespedes Feliciano EM, Kwan ML, Kushi LH,. Body mass index, PAM50 subtype, recurrence, and survival among patients with nonmetastatic breast cancer. Cancer. 2017;123(13):2535-2542

    Not in our library10.1002/cncr.30637

  96. 96.

    Clark W, Siegel EM, Chen YA,. Quantitative measures of visceral adiposity and body mass index in predicting rectal cancer outcomes after neoadjuvant chemoradiation. J Am Coll Surg. 2013;216(6):1070-1081

    Not in our library10.1016/j.jamcollsurg.2013.01.007

  97. 97.

    Dahdaleh FS, Sherman SK, Poli EC,. Obstruction predicts worse long-term outcomes in stage III colon cancer: a secondary analysis of the N0147 trial. Surgery. 2018;164(6):1223-1229

    Not in our library10.1016/j.surg.2018.06.044

  98. 98.

    Dignam JJ, Polite BN, Yothers G,. Body mass index and outcomes in patients who receive adjuvant chemotherapy for colon cancer. J Natl Cancer Inst. 2006;98(22):1647-1654

    Not in our library10.1093/jnci/djj442

  99. 99.

    Jayasekara H, English DR, Haydon A,. Associations of alcohol intake, smoking, physical activity and obesity with survival following colorectal cancer diagnosis by stage, anatomic site and tumor molecular subtype. Int J Cancer. 2018;142(2):238-250

    Not in our library10.1002/ijc.31049

  100. 100.

    Kaidar-Person O, Badarna H, Bar-Sela G. Bevacizumab for metastatic colon cancer: does patient BMI influence survival? Anticancer Drugs. 2015;26(3):363-366

    Not in our library10.1097/cad.0000000000000201

  101. 101.

    Kalb M, Langheinrich MC, Merkel S,. Influence of body mass index on long-term outcome in patients with rectal cancer-a single centre experience. Cancers (Basel). 2019;11(5):E609

    Not in our library10.3390/cancers11050609

  102. 102.

    Meyerhardt JA, Catalano PJ, Haller DG,. Influence of body mass index on outcomes and treatment-related toxicity in patients with colon carcinoma. Cancer. 2003;98(3):484-495

    Not in our library10.1002/cncr.11544

  103. 103.

    Meyerhardt JA, Tepper JE, Niedzwiecki D,. Impact of body mass index on outcomes and treatment-related toxicity in patients with stage II and III rectal cancer: findings from Intergroup Trial 0114. J Clin Oncol. 2004;22(4):648-657

    Not in our library10.1200/jco.2004.07.121

  104. 104.

    Meyerhardt JA, Niedzwiecki D, Hollis D,; Cancer and Leukemia Group B 89803. Impact of body mass index and weight change after treatment on cancer recurrence and survival in patients with stage III colon cancer: findings from Cancer and Leukemia Group B 89803. J Clin Oncol. 2008;26(25):4109-4115

    Not in our library10.1200/jco.2007.15.6687

  105. 105.

    Morikawa T, Kuchiba A, Liao X,. Tumor TP53 expression status, body mass index and prognosis in colorectal cancer. Int J Cancer. 2012;131(5):1169-1178

    Not in our library10.1002/ijc.26495

  106. 106.

    Ogino S, Nosho K, Baba Y,. A cohort study of STMN1 expression in colorectal cancer: body mass index and prognosis. Am J Gastroenterol. 2009;104(8):2047-2056

    Not in our library10.1038/ajg.2009.281

  107. 107.

    Patel GS, Ullah S, Beeke C,. Association of BMI with overall survival in patients with mCRC who received chemotherapy versus EGFR and VEGF-targeted therapies. Cancer Med. 2015;4(10):1461-1471

    Not in our library10.1002/cam4.490

  108. 108.

    Pelser C, Arem H, Pfeiffer RM,. Prediagnostic lifestyle factors and survival after colon and rectal cancer diagnosis in the National Institutes of Health (NIH)-AARP Diet and Health Study. Cancer. 2014;120(10):1540-1547

    Not in our library10.1002/cncr.28573

  109. 109.

    Prizment AE, Flood A, Anderson KE, Folsom AR. Survival of women with colon cancer in relation to precancer anthropometric characteristics: the Iowa Women’s Health Study. Cancer Epidemiol Biomarkers Prev. 2010;19(9):2229-2237

    Not in our library10.1158/1055-9965.epi-10-0522

  110. 110.

    Schlesinger S, Siegert S, Koch M,. Postdiagnosis body mass index and risk of mortality in colorectal cancer survivors: a prospective study and meta-analysis. Cancer Causes Control. 2014;25(10):1407-1418

    Not in our library10.1007/s10552-014-0435-x

  111. 111.

    Shah MS, Fogelman DR, Raghav KPS,. Joint prognostic effect of obesity and chronic systemic inflammation in patients with metastatic colorectal cancer. Cancer. 2015;121(17):2968-2975

    Not in our library10.1002/cncr.29440

  112. 112.

    Sinicrope FA, Foster NR, Yoon HH,. Association of obesity with DNA mismatch repair status and clinical outcome in patients with stage II or III colon carcinoma participating in NCCTG and NSABP adjuvant chemotherapy trials. J Clin Oncol. 2012;30(4):406-412

    Not in our library10.1200/jco.2011.39.2563

  113. 113.

    Sinicrope FA, Foster NR, Yothers G,; Adjuvant Colon Cancer Endpoints (ACCENT) Group. Body mass index at diagnosis and survival among colon cancer patients enrolled in clinical trials of adjuvant chemotherapy. Cancer. 2013;119(8):1528-1536

    Not in our library10.1002/cncr.27938

  114. 114.

    Sorbye H, Mauer M, Gruenberger T,; EORTC Gastro-Intestinal Tract Cancer Group; Cancer Research UK (CRUK); Arbeitsgruppe Lebermetastasen und-tumoren in der Chirurgischen Arbeitsgemeinschaft Onkologie (ALM-CAO); Australasian Gastro-Intestinal Trials Group (AGITG); Fédération Francophone de Cancérologie Digestive (FFCD). Predictive factors for the benefit of perioperative FOLFOX for resectable liver metastasis in colorectal cancer patients (EORTC Intergroup Trial 40983). Ann Surg. 2012;255(3):534-539

    Not in our library10.1097/sla.0b013e3182456aa2

  115. 115.

    Wang N, Khankari NK, Cai H,. Prediagnosis body mass index and waist-hip circumference ratio in association with colorectal cancer survival. Int J Cancer. 2017;140(2):292-301

    Not in our library10.1002/ijc.30459

  116. 116.

    Zheng J, Li Y, Zhu S,. NDRG4 stratifies the prognostic value of body mass index in colorectal cancer. Oncotarget. 2016;7(2):1311-1322

    Not in our library10.18632/oncotarget.6182

  117. 117.

    Doria-Rose VP, Newcomb PA, Morimoto LM, Hampton JM, Trentham-Dietz A. Body mass index and the risk of death following the diagnosis of colorectal cancer in postmenopausal women (United States). Cancer Causes Control. 2006;17(1):63-70

    Not in our library10.1007/s10552-005-0360-0

  118. 118.

    Kristensen AB, Hare-Bruun H, Høgdall CK, Rudnicki M. Influence of body mass index on tumor pathology and survival in uterine cancer: a Danish register study. Int J Gynecol Cancer. 2017;27(2):281-288

    Not in our library10.1097/igc.0000000000000874

  119. 119.

    Nagle CM, Crosbie EJ, Brand A,; Australian National Endometrial Cancer Study Group. The association between diabetes, comorbidities, body mass index and all-cause and cause-specific mortality among women with endometrial cancer. Gynecol Oncol. 2018;150(1):99-105

    Not in our library10.1016/j.ygyno.2018.04.006

  120. 120.

    Nicholas Z, Hu N, Ying J, Soisson P, Dodson M, Gaffney DK. Impact of comorbid conditions on survival in endometrial cancer. Am J Clin Oncol. 2014;37(2):131-134

    Not in our library10.1097/coc.0b013e318277d5f4

  121. 121.

    Todo Y, Okamoto K, Minobe S, Kato H. Clinical significance of surgical staging for obese women with endometrial cancer: a retrospective analysis in a Japanese cohort. Jpn J Clin Oncol. 2014;44(10):903-909

    Not in our library10.1093/jjco/hyu106

  122. 122.

    Yoon LS, Goodman MT, Rimel BJ, Jeon CY. Statin use and survival in elderly patients with endometrial cancer. Gynecol Oncol. 2015;137(2):252-257

    Not in our library10.1016/j.ygyno.2015.01.549

  123. 123.

    Hynes O, Anandavadivelan P, Gossage J, Johar AM, Lagergren J, Lagergren P. The impact of pre- and post-operative weight loss and body mass index on prognosis in patients with oesophageal cancer. Eur J Surg Oncol. 2017;43(8):1559-1565

    Not in our library10.1016/j.ejso.2017.05.023

  124. 124.

    Spreafico A, Coate L, Zhai R,. Early adulthood body mass index, cumulative smoking, and esophageal adenocarcinoma survival. Cancer Epidemiol. 2017;47:28-34

    Not in our library10.1016/j.canep.2016.11.009

  125. 125.

    Sundelöf M, Lagergren J, Ye W. Patient demographics and lifestyle factors influencing long-term survival of oesophageal cancer and gastric cardia cancer in a nationwide study in Sweden. Eur J Cancer. 2008;44(11):1566-1571

    Not in our library10.1016/j.ejca.2008.04.002

  126. 126.

    Yoon HH, Lewis MA, Shi Q,. Prognostic impact of body mass index stratified by smoking status in patients with esophageal adenocarcinoma. J Clin Oncol. 2011;29(34):4561-4567

    Not in our library10.1200/jco.2011.37.1260

  127. 127.

    Thrift AP, Nagle CM, Fahey PP, Smithers BM, Watson DI, Whiteman DC. Predictors of survival among patients diagnosed with adenocarcinoma of the esophagus and gastroesophageal junction. Cancer Causes Control. 2012;23(4):555-564

    Not in our library10.1007/s10552-012-9913-1

  128. 128.

    Trivers KF, De Roos AJ, Gammon MD,. Demographic and lifestyle predictors of survival in patients with esophageal or gastric cancers. Clin Gastroenterol Hepatol. 2005;3(3):225-230

    Not in our library10.1016/s1542-3565(04)00613-5

  129. 129.

    Potharaju M, Mangaleswaran B, Mathavan A,. Body mass index as a prognostic marker in glioblastoma multiforme: a clinical outcome. Int J Radiat Oncol Biol Phys. 2018;102(1):204-209

    Not in our library10.1016/j.ijrobp.2018.05.024

  130. 130.

    Gama RR, Song Y, Zhang Q,. Body mass index and prognosis in patients with head and neck cancer. Head Neck. 2017;39(6):1226-1233

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  131. 131.

    Grossberg AJ, Chamchod S, Fuller CD,. Association of body composition with survival and locoregional control of radiotherapy-treated head and neck squamous cell carcinoma. JAMA Oncol. 2016;2(6):782-789

    Not in our library10.1001/jamaoncol.2015.6339

  132. 132.

    Hu Q, Peng J, Chen X,. Obesity and genes related to lipid metabolism predict poor survival in oral squamous cell carcinoma. Oral Oncol. 2019;89:14-22

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    Ata N, Ayloo S, Tsung A, Molinari M. Recipient obesity does not affect survival after deceased donor liver transplantation for hepatocellular carcinoma: a national retrospective cohort study in the United States. HPB (Oxford). 2019;21(1):67-76

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    Carr BI, Giannelli G, Guerra V,. Plasma cholesterol and lipoprotein levels in relation to tumor aggressiveness and survival in HCC patients. Int J Biol Markers. 2018;33(4):423-431

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  135. 135.

    Yang T, Liu K, Liu CF,. Impact of postoperative infective complications on long-term survival after liver resection for hepatocellular carcinoma. Br J Surg. 2019;106(9):1228-1236

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  136. 136.

    Roque DR, Taylor KN, Palisoul M,. Gemcitabine and docetaxel compared with observation, radiation, or other chemotherapy regimens as adjuvant treatment for stage I-to-IV uterine leiomyosarcoma. Int J Gynecol Cancer. 2016;26(3):505-511

    Not in our library10.1097/igc.0000000000000634

  137. 137.

    McMahon BJ, Bruden D, Townshend-Bulson L,. Infection With hepatitis C virus genotype 3 is an independent risk factor for end-stage liver disease, hepatocellular carcinoma, and liver-related death. Clin Gastroenterol Hepatol. 2017;15(3):431-437.e2

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  138. 138.

    Abdel-Rahman O. Pre-diagnostic body mass index trajectory in relationship to lung cancer incidence and mortality; findings from the PLCO trial. Expert Rev Respir Med. 2019;13(10):1029-1035

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    Leung CC, Lam TH, Yew WW, Chan WM, Law WS, Tam CM. Lower lung cancer mortality in obesity. Int J Epidemiol. 2011;40(1):174-182

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    Nonemaker JM, Garrett-Mayer E, Carpenter MJ,. The risk of dying from lung cancer by race: a prospective cohort study in a biracial cohort in Charleston, South Carolina. Ann Epidemiol. 2009;19(5):304-310

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    Qi Y, Schild SE, Mandrekar SJ,. Pretreatment quality of life is an independent prognostic factor for overall survival in patients with advanced stage non-small cell lung cancer. J Thorac Oncol. 2009;4(9):1075-1082

    Not in our library10.1097/jto.0b013e3181ae27f5

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    Shepshelovich D, Xu W, Lu L,. Body mass index (BMI), BMI change, and overall survival in patients with SCLC and NSCLC: a pooled analysis of the International Lung Cancer Consortium. J Thorac Oncol. 2019;14(9):1594-1607

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    Turner MC, Krewski D, Pope CA III, Chen Y, Gapstur SM, Thun MJ. Long-term ambient fine particulate matter air pollution and lung cancer in a large cohort of never-smokers. Am J Respir Crit Care Med. 2011;184(12):1374-1381

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    Effect of body mass index on survival of patients with stage I non-small cell lung cancer · 2017
    Not checked
  145. 145.

    McQuade JL, Daniel CR, Hess PKR,. Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: a retrospective, multicohort analysis. Lancet Oncol. 2018;19(3):310-322

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    Aldrich MC, Grogan EL, Munro HM, Signorello LB, Blot WJ. Stage-adjusted lung cancer survival does not differ between low-income Blacks and Whites. J Thorac Oncol. 2013;8(10):1248-1254

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    Kichenadasse G, Miners JO, Mangoni AA, Rowland A, Hopkins AM, Sorich MJ. Association between body mass index and overall survival with immune checkpoint inhibitor therapy for advanced non-small cell lung cancer. JAMA Oncol. 2020;6(4):512-518

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    Nakagawa T, Toyazaki T, Chiba N, Ueda Y, Gotoh M. Prognostic value of body mass index and change in body weight in postoperative outcomes of lung cancer surgery. Interact Cardiovasc Thorac Surg. 2016;23(4):560-566

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    Bandera EV, Lee VS, Rodriguez-Rodriguez L, Powell CB, Kushi LH. Impact of chemotherapy dosing on ovarian cancer survival according to body mass index. JAMA Oncol. 2015;1(6):737-745

    Not in our library10.1001/jamaoncol.2015.1796

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    Kotsopoulos J, Moody JRK, Fan I,. Height, weight, BMI and ovarian cancer survival. Gynecol Oncol. 2012;127(1):83-87

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    Minlikeeva AN, Cannioto R, Jensen A,; Australian Ovarian Cancer Study Group; Ovarian Cancer Association Consortium. Joint exposure to smoking, excessive weight, and physical inactivity and survival of ovarian cancer patients, evidence from the Ovarian Cancer Association Consortium. Cancer Causes Control. 2019;30(5):537-547

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  152. 152.

    Previs RA, Kilgore J, Craven R,. Obesity is associated with worse overall survival in women with low-grade papillary serous epithelial ovarian cancer. Int J Gynecol Cancer. 2014;24(4):670-675

    Not in our library10.1097/igc.0000000000000109

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    Tyler CP, Whiteman MK, Zapata LB,. The effect of body mass index and weight change on epithelial ovarian cancer survival in younger women: a long-term follow-up study. J Womens Health (Larchmt). 2012;21(8):865-871

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    Yang L, Klint A, Lambe M,. Predictors of ovarian cancer survival: a population-based prospective study in Sweden. Int J Cancer. 2008;123(3):672-679

    Not in our library10.1002/ijc.23429

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    Dalal S, Hui D, Bidaut L,. Relationships among body mass index, longitudinal body composition alterations, and survival in patients with locally advanced pancreatic cancer receiving chemoradiation: a pilot study. J Pain Symptom Manage. 2012;44(2):181-191

    Not in our library10.1016/j.jpainsymman.2011.09.010

  156. 156.

    Genkinger JM, Kitahara CM, Bernstein L,. Central adiposity, obesity during early adulthood, and pancreatic cancer mortality in a pooled analysis of cohort studies. Ann Oncol. 2015;26(11):2257-2266

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    Gong Z, Holly EA, Bracci PM. Obesity and survival in population-based patients with pancreatic cancer in the San Francisco Bay Area. Cancer Causes Control. 2012;23(12):1929-1937

    Not in our library10.1007/s10552-012-0070-3

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    Li D, Morris JS, Liu J,. Body mass index and risk, age of onset, and survival in patients with pancreatic cancer. JAMA. 2009;301(24):2553-2562.

    Not in our library10.1001/jama.2009.886

  159. 159.

    Lin Y, Fu R, Grant E,. Association of body mass index and risk of death from pancreas cancer in Asians: findings from the Asia Cohort Consortium. Eur J Cancer Prev. 2013;22(3):244-250

    Not in our library10.1097/cej.0b013e3283592cef

  160. 160.

    Olson SH, Chou JF, Ludwig E,. Allergies, obesity, other risk factors and survival from pancreatic cancer. Int J Cancer. 2010;127(10):2412-2419

    Not in our library10.1002/ijc.25240

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    Yuan C, Bao Y, Wu C,. Prediagnostic body mass index and pancreatic cancer survival. J Clin Oncol. 2013;31(33):4229-4234

    Not in our library10.1200/jco.2013.51.7532

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    Tsai S, Choti MA, Assumpcao L,. Impact of obesity on perioperative outcomes and survival following pancreaticoduodenectomy for pancreatic cancer: a large single-institution study. J Gastrointest Surg. 2010;14(7):1143-1150

    Not in our library10.1007/s11605-010-1201-3

  163. 163.

    Bassett JK, Severi G, Baglietto L,. Weight change and prostate cancer incidence and mortality. Int J Cancer. 2012;131(7):1711-1719

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    Bonn SE, Wiklund F, Sjölander A,. Body mass index and weight change in men with prostate cancer: progression and mortality. Cancer Causes Control. 2014;25(8):933-943

    Not in our library10.1007/s10552-014-0393-3

  165. 165.

    Dickerman BA, Ahearn TU, Giovannucci E,. Weight change, obesity and risk of prostate cancer progression among men with clinically localized prostate cancer. Int J Cancer. 2017;141(5):933-944

    Not in our library10.1002/ijc.30803

  166. 166.

    Efstathiou JA, Bae K, Shipley WU,. Obesity and mortality in men with locally advanced prostate cancer: analysis of RTOG 85-31. Cancer. 2007;110(12):2691-2699

    Not in our library10.1002/cncr.23093

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    Farris MS, Courneya KS, Kopciuk KA, McGregor SE, Friedenreich CM. Anthropometric measurements and survival after a prostate cancer diagnosis. Br J Cancer. 2018;118(4):607-610

    Not in our library10.1038/bjc.2017.440

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    Froehner M, Kellner AE, Koch R, Baretton GB, Hakenberg OW, Wirth MP. A combined index to classify prognostic comorbidity in candidates for radical prostatectomy. BMC Urol. 2014;14(1):28

    Not in our library10.1186/1471-2490-14-28

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    Gong Z, Agalliu I, Lin DW, Stanford JL, Kristal AR. Obesity is associated with increased risks of prostate cancer metastasis and death after initial cancer diagnosis in middle-aged men. Cancer. 2007;109(6):1192-1202

    Not in our library10.1002/cncr.22534

  170. 170.

    Han M, Trock BJ, Partin AW,. The impact of preoperative erectile dysfunction on survival after radical prostatectomy. BJU Int. 2010;106(11):1612-1617

    Not in our library10.1111/j.1464-410x.2010.09472.x

  171. 171.

    Ho T, Gerber L, Aronson WJ,. Obesity, prostate-specific antigen nadir, and biochemical recurrence after radical prostatectomy: biology or technique? results from the SEARCH database. Eur Urol. 2012;62(5):910-916

    Not in our library10.1016/j.eururo.2012.08.015

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    Kelly SP, Graubard BI, Andreotti G, Younes N, Cleary SD, Cook MB. Prediagnostic body mass index trajectories in relation to prostate cancer incidence and mortality in the PLCO cancer screening trial. J Natl Cancer Inst. 2016;109(3):1-9

    Not in our library10.1093/jnci/djw225

  173. 173.

    Kenfield SA, Batista JL, Jahn JL,. Development and application of a lifestyle score for prevention of lethal prostate cancer. J Natl Cancer Inst. 2015;108(3):djv329

    Not in our library10.1093/jnci/djv329

  174. 174.

    Khan S, Cai J, Nielsen ME,. The association of diabetes and obesity with prostate cancer progression: HCaP-NC. Prostate. 2017;77(8):878-887

    Not in our library10.1002/pros.23342

  175. 175.

    Ma J, Li H, Giovannucci E,. Prediagnostic body-mass index, plasma C-peptide concentration, and prostate cancer-specific mortality in men with prostate cancer: a long-term survival analysis. Lancet Oncol. 2008;9(11):1039-1047

    Not in our library10.1016/s1470-2045(08)70235-3

  176. 176.

    Maj-Hes AB, Mathieu R, Özsoy M,. Obesity is associated with biochemical recurrence after radical prostatectomy: a multi-institutional extended validation study. Urol Oncol. 2017;35(7):460.e1-460.e8

    Not in our library10.1016/j.urolonc.2017.01.022

  177. 177.

    Møller H, Roswall N, Van Hemelrijck M,. Prostate cancer incidence, clinical stage and survival in relation to obesity: a prospective cohort study in Denmark. Int J Cancer. 2015;136(8):1940-1947

    Not in our library10.1002/ijc.29238

  178. 178.

    Rudman SM, Gray KP, Batista JL,. Risk of prostate cancer-specific death in men with baseline metabolic aberrations treated with androgen deprivation therapy for biochemical recurrence. BJU Int. 2016;118(6):919-926

    Not in our library10.1111/bju.13428

  179. 179.

    Schiffmann J, Salomon G, Tilki D,. Radical prostatectomy neutralizes obesity-driven risk of prostate cancer progression. Urol Oncol. 2017;35(5):243-249

    Not in our library10.1016/j.urolonc.2016.12.014

  180. 180.

    Spangler E, Zeigler-Johnson CM, Coomes M, Malkowicz SB, Wein A, Rebbeck TR. Association of obesity with tumor characteristics and treatment failure of prostate cancer in African-American and European American men. J Urol. 2007;178(5):1939-1944

    Not in our library10.1016/j.juro.2007.07.021

  181. 181.

    Vidal AC, Howard LE, Sun SX,. Obesity and prostate cancer-specific mortality after radical prostatectomy: results from the Shared Equal Access Regional Cancer Hospital (SEARCH) database. Prostate Cancer Prostatic Dis. 2017;20(1):72-78

    Not in our library10.1038/pcan.2016.47

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    Wu W, Liu X, Chaftari P,. Association of body composition with outcome of docetaxel chemotherapy in metastatic prostate cancer: a retrospective review. PLoS One. 2015;10(3):e0122047

    Not in our library10.1371/journal.pone.0122047

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    Montgomery RB, Goldman B, Tangen CM,; Southwest Oncology Group. Association of body mass index with response and survival in men with metastatic prostate cancer: Southwest Oncology Group trials 8894 and 9916. J Urol. 2007;178(5):1946-1951

    Not in our library10.1016/j.juro.2007.07.026

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    Halabi S, Ou SS, Vogelzang NJ, Small EJ. Inverse correlation between body mass index and clinical outcomes in men with advanced castration-recurrent prostate cancer. Cancer. 2007;110(7):1478-1484

    Not in our library10.1002/cncr.22932

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    Keizman D, Gottfried M, Ish-Shalom M,. Active smoking may negatively affect response rate, progression-free survival, and overall survival of patients with metastatic renal cell carcinoma treated with sunitinib. Oncologist. 2014;19(1):51-60

    Not in our library10.1634/theoncologist.2012-0335

  186. 186.

    Lee WK, Byun SS, Kim HH,. Characteristics and prognosis of chromophobe non-metastatic renal cell carcinoma: a multicenter study. Int J Urol. 2010;17(11):898-904

    Not in our library10.1111/j.1442-2042.2010.02630.x

  187. 187.

    Parker AS, Lohse CM, Cheville JC, Thiel DD, Leibovich BC, Blute ML. Greater body mass index is associated with better pathologic features and improved outcome among patients treated surgically for clear cell renal cell carcinoma. Urology. 2006;68(4):741-746

    Not in our library10.1016/j.urology.2006.05.024

  188. 188.

    Psutka SP, Boorjian SA, Moynagh MR,. Decreased skeletal muscle mass is associated with an increased risk of mortality after radical nephrectomy for localized renal cell cancer. J Urol. 2016;195(2):270-276

    Not in our library10.1016/j.juro.2015.08.072

  189. 189.

    Spiess PE, Kurian T, Lin HY,. Preoperative metastatic status, level of thrombus and body mass index predict overall survival in patients undergoing nephrectomy and inferior vena cava thrombectomy. BJU Int. 2012;110(11 Pt B):E470-E474

    Not in our library10.1111/j.1464-410x.2012.11155.x

  190. 190.

    Yu ML, Asal NR, Geyer JR. Later recurrence and longer survival among obese patients with renal cell carcinoma. Cancer. 1991;68(7):1648-1655

    Not in our library10.1002/1097-0142(19911001)68:7<1648:aid-cncr2820680731>3.0.co;2-5

  191. 191.

    Hung CY, Lai CC, Chen PT,. Impact of body mass index on long-term survival outcome in Asian populations with solid cancer who underwent curative-intent surgery: a six-year multicenter observational cohort study. J Cancer. 2018;9(18):3316-3325

    Not in our library10.7150/jca.25729

  192. 192.

    Houdek MT, Griffin AM, Ferguson PC, Wunder JS. Morbid obesity increases the risk of postoperative wound complications, infection, and repeat surgical procedures following upper extremity limb salvage surgery for soft tissue sarcoma. Hand (N Y). 2019;14(1):114-120

    Not in our library10.1177/1558944718797336

  193. 193.

    Iyengar NM, Kochhar A, Morris PG,. Impact of obesity on the survival of patients with early‐stage squamous cell carcinoma of the oral tongue. Cancer. 2014;120(7):983-991

    Not in our library10.1002/cncr.28532

  194. 194.

    Xu H, Tan P, Zheng X,. Metabolic syndrome and upper tract urothelial carcinoma: A retrospective analysis from a large Chinese cohort. Urol Oncol. 2019;37(4):291.e19-291.e28

    Not in our library10.1016/j.urolonc.2018.12.005

  195. 195.

    Arem H, Park Y, Pelser C,. Prediagnosis body mass index, physical activity, and mortality in endometrial cancer patients. J Natl Cancer Inst. 2013;105(5):342-349

    Not in our library10.1093/jnci/djs530

  196. 196.

    Matsuo K, Moeini A, Cahoon SS,. Weight change pattern and survival outcome of women with endometrial cancer. Ann Surg Oncol. 2016;23(9):2988-2997

    Not in our library10.1245/s10434-016-5237-9

  197. 197.

    Ruterbusch JJ, Ali-Fehmi R, Olson SH,. The influence of comorbid conditions on racial disparities in endometrial cancer survival. Am J Obstet Gynecol. 2014;211(6):627.e1-627.e9

    Not in our library10.1016/j.ajog.2014.06.036

  198. 198.

    Seidelin UH, Ibfelt E, Andersen I,. Does stage of cancer, comorbidity or lifestyle factors explain educational differences in survival after endometrial cancer? a cohort study among Danish women diagnosed 2005-2009. Acta Oncol. 2016;55(6):680-685

    Not in our library10.3109/0284186x.2015.1136750

  199. 199.

    Abdullah A, Wolfe R, Stoelwinder JU,. The number of years lived with obesity and the risk of all-cause and cause-specific mortality. Int J Epidemiol. 2011;40(4):985-996

    Not in our library10.1093/ije/dyr018

  200. 200.

    Akinyemiju T, Moore JX, Pisu M,. A prospective study of obesity, metabolic health, and cancer mortality. Obesity (Silver Spring). 2018;26(1):193-201

    Not in our library10.1002/oby.22067.a

  201. 201.

    Barroso M, Goday A, Ramos R,; FRESCO Investigators. Interaction between cardiovascular risk factors and body mass index and 10-year incidence of cardiovascular disease, cancer death, and overall mortality. Prev Med. 2018;107(107):81-89

    Not in our library10.1016/j.ypmed.2017.11.013

  202. 202.

    Boggs DA, Rosenberg L, Cozier YC,. General and abdominal obesity and risk of death among black women. N Engl J Med. 2011;365(10):901-908

    Not in our library10.1056/nejmoa1104119

  203. 203.
    A multicenter study of body mass index in cancer patients treated with anti-PD-1/PD-L1 immune checkpoint inhibitors: when overweight becomes favorable · 2019
    No notice
  204. 204.

    Drake I, Gullberg B, Sonestedt E,. Type 2 diabetes, adiposity and cancer morbidity and mortality risk taking into account competing risk of noncancer deaths in a prospective cohort setting. Int J Cancer. 2017;141(6):1170-1180

    Not in our library10.1002/ijc.30824

  205. 205.

    Han X, Stevens J, Truesdale KP,. Body mass index at early adulthood, subsequent weight change and cancer incidence and mortality. Int J Cancer. 2014;135(12):2900-2909

    Not in our library10.1002/ijc.28930

  206. 206.

    Izumida T, Nakamura Y, Ishikawa S. Impact of body mass index and metabolically unhealthy status on mortality in the Japanese general population: the JMS cohort study. PLoS One. 2019;14(11):e0224802

    Not in our library10.1371/journal.pone.0224802

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    Janssen SJ, van der Heijden AS, van Dijke M,. 2015 Marshall Urist Young Investigator Award: prognostication in patients with long bone metastases: does a boosting algorithm improve survival estimates? Clin Orthop Relat Res. 2015;473(10):3112-3121

    Not in our library10.1007/s11999-015-4446-z

  208. 208.

    Jenkins DA, Bowden J, Robinson HA,. Adiposity-mortality relationships in type 2 diabetes, coronary heart disease, and cancer subgroups in the UK Biobank, and their modification by smoking. Diabetes Care. 2018;41(9):1878-1886

    Not in our library10.2337/dc17-2508

  209. 209.

    Katzmarzyk PT, Reeder BA, Elliott S,. Body mass index and risk of cardiovascular disease, cancer and all-cause mortality. Can J Public Health. 2012;103(2):147-151

    Not in our library10.1007/bf03404221

  210. 210.
    Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality: A Pooled Analysis of 20 Prospective Studies · 2014
    No notice
  211. 211.

    Martini DJ, Kline MR, Liu Y,. Adiposity may predict survival in patients with advanced stage cancer treated with immunotherapy in phase 1 clinical trials. Cancer. 2020;126(3):575-582

    Not in our library10.1002/cncr.32576

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    Mathur AK, Ghaferi AA, Sell K, Sonnenday CJ, Englesbe MJ, Welling TH. Influence of body mass index on complications and oncologic outcomes following hepatectomy for malignancy. J Gastrointest Surg. 2010;14(5):849-857

    Not in our library10.1007/s11605-010-1163-5

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    Meyer J, Rohrmann S, Bopp M, Faeh D; Swiss National Cohort Study Group. Impact of smoking and excess body weight on overall and site-specific cancer mortality risk. Cancer Epidemiol Biomarkers Prev. 2015;24(10):1516-1522

    Not in our library10.1158/1055-9965.epi-15-0415

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    Nechuta SJ, Shu XO, Li HL,. Combined impact of lifestyle-related factors on total and cause-specific mortality among Chinese women: prospective cohort study. PLoS Med. 2010;7(9):e1000339

    Not in our library10.1371/journal.pmed.1000339

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    Parr CL, Batty GD, Lam TH,; Asia-Pacific Cohort Studies Collaboration. Body-mass index and cancer mortality in the Asia-Pacific Cohort Studies Collaboration: pooled analyses of 424,519 participants. Lancet Oncol. 2010;11(8):741-752

    Not in our library10.1016/s1470-2045(10)70141-8

  216. 216.

    Sasazuki S, Inoue M, Tsuji I,; Research Group for the Development and Evaluation of Cancer Prevention Strategies in Japan. Body mass index and mortality from all causes and major causes in Japanese: results of a pooled analysis of 7 large-scale cohort studies. J Epidemiol. 2011;21(6):417-430

    Not in our library10.2188/jea.je20100180

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    Silventoinen K, Tynelius P, Rasmussen F. Weight status in young adulthood and survival after cardiovascular diseases and cancer. Int J Epidemiol. 2014;43(4):1197-1204

    Not in our library10.1093/ije/dyu091

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    Song X, Pitkäniemi J, Gao W,; DECODE Study Group. Relationship between body mass index and mortality among Europeans. Eur J Clin Nutr. 2012;66(2):156-165

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    BMI and lifetime changes in BMI and cancer mortality risk. · 2015
    Not checked
  220. 220.

    Tseng CH. Obesity paradox: differential effects on cancer and noncancer mortality in patients with type 2 diabetes mellitus. Atherosclerosis. 2013;226(1):186-192

    Not in our library10.1016/j.atherosclerosis.2012.09.004

  221. 221.

    Tseng CH. Factors associated with cancer- and non-cancer-related deaths among Taiwanese patients with diabetes after 17 years of follow-up. PLoS One. 2016;11(12):e0147916

    Not in our library10.1371/journal.pone.0147916

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    Valentijn TM, Galal W, Hoeks SE, van Gestel YR, Verhagen HJ, Stolker RJ. Impact of obesity on postoperative and long-term outcomes in a general surgery population: a retrospective cohort study. World J Surg. 2013;37(11):2561-2568

    Not in our library10.1007/s00268-013-2162-y

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    Association of Obesity With Mortality Over 24 Years of Weight History · 2018
    No notice
  224. 224.

    Yano Y, Kario K, Ishikawa S,; JMS Cohort Study Group. Associations between diabetes, leanness, and the risk of death in the Japanese general population: the Jichi Medical School Cohort Study. Diabetes Care. 2013;36(5):1186-1192

    Not in our library10.2337/dc12-1736

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    You J, Huang S, Huang GQ,. Nonalcoholic fatty liver disease: a negative risk factor for colorectal cancer prognosis. Medicine (Baltimore). 2015;94(5):e479

    Not in our library10.1097/md.0000000000000479

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    Key TJ, Appleby PN, Reeves GK,; Endogenous Hormones Breast Cancer Collaborative Group. Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women. J Natl Cancer Inst. 2003;95(16):1218-1226

    Not in our library10.1093/jnci/djg022

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    Campbell KL, Foster-Schubert KE, Alfano CM,. Reduced-calorie dietary weight loss, exercise, and sex hormones in postmenopausal women: randomized controlled trial. J Clin Oncol. 2012;30(19):2314-2326

    Not in our library10.1200/jco.2011.37.9792

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    Campbell PT, Newton CC, Dehal AN, Jacobs EJ, Patel AV, Gapstur SM. Impact of body mass index on survival after colorectal cancer diagnosis: the Cancer Prevention Study-II Nutrition Cohort. J Clin Oncol. 2012;30(1):42-52

    Not in our library10.1200/jco.2011.38.0287

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    Renehan AG, Roberts DL, Dive C. Obesity and cancer: pathophysiological and biological mechanisms. Arch Physiol Biochem. 2008;114(1):71-83

    Not in our library10.1080/13813450801954303

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    Lippman SM, Klein EA, Goodman PJ,. Effect of selenium and vitamin E on risk of prostate cancer and other cancers: The selenium and vitamin E cancer prevention trial (SELECT). JAMA. 2009;301(1):39-51

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