Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Null Results in Brief

Usual Adult Body Mass Index Is Not Predictive of Ovarian Cancer Survival

Kirsten B. Moysich, Julie A. Baker, Ravi J. Menezes, Vijayvel Jayaprakash, Kerry J. Rodabaugh, Kunle Odunsi, Gregory P. Beehler, Susan E. McCann and Jeannine A. Villella
Kirsten B. Moysich
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Julie A. Baker
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ravi J. Menezes
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vijayvel Jayaprakash
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kerry J. Rodabaugh
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kunle Odunsi
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gregory P. Beehler
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Susan E. McCann
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jeannine A. Villella
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/1055-9965.EPI-06-1052 Published March 2007
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading
  • body mass index
  • ovarian cancer
  • prognosis

Introduction

Although obesity has been proposed as both a risk factor and prognostic factor for hormonally mediated cancers such as endometrial and breast, it is less clear whether this also applies to ovarian cancer (1). In addition, some authors have suggested that obese patients may receive potentially subtherapeutic doses of chemotherapy, when the calculated chemotherapy dose (based on body weight) exceeds the maximum dose patients (1). Large cohort studies have shown higher ovarian cancer mortality with increasing body mass index (BMI); however, these studies could not differentiate obesity's effect on cancer incidence from the effect on prognosis (1-3). Three recent studies have suggested that obesity may be associated with worse prognosis among ovarian cancer patients (4-6), whereas one study did not identify an association (7). To address this issue, the current study investigated whether survival differed by premorbid BMI among women with ovarian cancer treated at Roswell Park Cancer Institute (RPCI) in Buffalo, NY.

Materials and Methods

The study population included 409 patients diagnosed at RPCI between 1982 and 1998 who also completed a comprehensive epidemiologic questionnaire. Details about the data collection and study population have been described elsewhere (8-11). Briefly, as part of this 16-page questionnaire, patients were prompted to report their current height, current weight, and usual weight before diagnosis. Information on the survival, staging, and treatment was obtained from the RPCI tumor registry and was matched to questionnaire information. Medical records were also reviewed to collect additional clinical data, including information on past medical history [notably hypertension, diabetes, thyroid problems, and gastroesophageal reflux disease (GERD)]. These conditions have the potential to confound the association between BMI and survival because they are known to be associated with BMI and are also associated with increased toxicity and decreased tolerance of chemotherapy, potentially worsening ovarian cancer prognosis. Because complete information on the adequacy of cytoreduction was not identified in the majority of patients' medical records, this prognostic characteristic was not included in the current analysis. Usual BMI was calculated as weight (in kilograms) divided by height (in meters) squared. Patients were categorized as underweight (BMI <18.5), normal weight (BMI 18.5-24.9), overweight (BMI 25.0-29.9), and obese (BMI ≥30.0). As few individuals were underweight (n = 8), these individuals were combined with normal weight patients and were used as the reference group for all analyses. Patients with incomplete information on either usual BMI or survival were excluded (n = 14), resulting in the analysis of 395 ovarian cancer patients.

Survival time was calculated in months from date of diagnosis to date of death, loss to follow-up, or March 2006. Eighty-nine percent of all deaths were due to ovarian cancer. Kaplan-Meier curves were used to compare survival by BMI category, and differences were tested with the log-rank test. Hazard ratios (HR) and 95% confidence intervals (95% CI) were computed using Cox regression, and the proportional hazard assumption was confirmed for all covariates. Characteristics that were associated with prognosis were considered candidates for inclusion in adjusted models using a forward selection technique. Because 36 individuals lacked information on at least one covariate, 359 individuals were included in adjusted models.

Results

After a minimum of 9 years of follow-up, 300 of the 395 women with ovarian cancer were deceased. Table 1 displays potential prognostic characteristics by vital status, confirming the role of established factors such as age at diagnosis, Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage, tumor grade, and histologic subtype. Consistent with previous studies, platinum-based chemotherapy was associated with worse survival, likely as a marker of more severe disease. Evaluation of past medical history revealed a worse prognosis for individuals with a history of diabetes or GERD. No association was noted between survival and other medical conditions.

View this table:
  • View inline
  • View popup
Table 1.

Characteristics of 395 ovarian cancer patients, by survival status, RPCI

As displayed in Table 2 , ovarian cancer survival was not associated with being overweight (adjusted HR, 1.01; 95% CI, 0.76-1.34) or obese (adjusted HR, 0.94; 95% CI, 0.68-1.30). When BMI was examined in a continuous manner, no linear association was noted with unit increases in BMI (adjusted HR, 1.00; 95% CI, 0.98-1.02). Results did not differ when analyses were stratified by stage, grade, histologic subtype, or age at diagnosis, nor did they differ when analyses were repeated using disease-specific death as the outcome of interest (data not shown).

View this table:
  • View inline
  • View popup
Table 2.

Ovarian cancer survival by usual BMI, RPCI

Discussion

In this follow-up study of 395 women with ovarian cancer, survival was not associated with usual adult BMI. To our knowledge, only four studies have been published, which examined BMI specifically as a potential prognostic factor for women with ovarian cancer (4-7). The first, in 2000, found no association between obesity (defined as BMI >27.9 kg/m2) and crude survival in a cohort of 257 U.S. women with invasive or borderline ovarian tumors (7). In contrast, a cohort of 207 Chinese ovarian cancer patients found an association between self-reported BMI 5 years before diagnosis and mortality; compared with individuals with a BMI <20, increased mortality was suggested for women whose BMI was 20.0 to 22.4 (HR, 1.79; 95% CI, 0.90-3.55), 22.5 to 24.9 (HR, 1.71; 95% CI, 0.84-3.46), or ≥25.0 (HR, 2.33; 95% CI, 1.12-4.87; ref. 5). However, mortality was not associated with either BMI at age 21 or BMI at diagnosis, and the study included few individuals who were either overweight or obese. A medical record review of 216 U.S. ovarian cancer patients reported by Pavelka et al. identified a statistically significant linear association between BMI and either cancer recurrence (HR, 1.04) or death (HR, 1.05), although interpretations were complicated by the use of postoperative BMI, which may not be representative of premorbid BMI (6). Lastly, a follow-up of 295 Danish women with stage III ovarian cancer who participated in the Malignant Ovarian Cancer (MALOVA) study found increased mortality for individuals who were obese 5 years before diagnosis (HR, 1.83; 95% CI, 1.38-2.42; HR per unit increase in BMI, 1.05; 95% CI, 1.02-1.08) but no association with BMI at age 20 to 29 (4).

It is unclear whether results differ between studies due to varying degrees of obesity in the study population, changing biological effects based on the time period under investigation, or due to confounding by other important prognostic factors. For example, obesity has the potential to affect prognosis through other mechanisms. Some authors have speculated that obese patients may receive inadequate surgery, although two studies have shown that obese patients were equally likely to have optimal surgical cytoreduction (6, 13). In addition, difficulty determining the optimal chemotherapy dose may result in suboptimal treatment for obese patients (1). However, lower dosing also has the ability to minimize toxicity, improving tolerability of chemotherapy.

The current study has several limitations. Most notably, analyses were based on self-reported usual adult BMI. As such, we were unable to assess whether BMI at particular time periods would be more relevant. In addition, although participants were instructed to report their premorbid weight, it is possible that estimates were influenced by subtle weight changes before diagnosis. The current study also lacked information on adequacy of cytoreduction, an important prognostic factor. However, other prognostic factors were well documented, and previous studies have suggested that adequacy of cytoreduction does not differ as a function of BMI (6, 12, 13). In addition, a small proportion of people were excluded from the study for missing information on BMI or were excluded from adjusted analyses due to missing information on covariates. However, these numbers are small and unlikely to be responsible for the null finding observed.

However, the current study also has several strengths, including the long length of follow-up (between 9 and 23 years) and a larger cohort than other studies of this nature. Power estimates were calculated using software developed by Dupont and Plummer (14) based upon the following conditions: α = 0.05, 77 obese patients, median survival time of 57 months for normal weight patients, 192 months of study accrual, 87 months of additional follow-up time, and a ratio of 210:77 normal weight/obese patients. Under these conditions, the study had 80% power to detect an HR of 1.52 for obese patients, and 99% power to detect a HR of 2.0. As such, the study was adequately powered to detect differences of the magnitude noted in previous studies.

In summary, the current study did not identify an association between ovarian cancer survival and being overweight or obese. Further research is warranted to investigate the potential role of obesity in ovarian cancer prognosis.

Footnotes

  • The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

    • Accepted January 5, 2007.
    • Received December 20, 2006.

References

  1. ↵
    Modesitt SC, van Nagell JR, Jr. The impact of obesity on the incidence and treatment of gynecologic cancers: a review. Obstet Gynecol Surv 2005;60:683–92.
    OpenUrlCrossRefPubMed
  2. Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults [see comment]. N Engl J Med 2003;348:1625–38.
    OpenUrlCrossRefPubMed
  3. ↵
    Rodriguez C, Calle EE, Fakhrabadi-Shokoohi D, Jacobs EJ, Thun MJ. Body mass index, height, and the risk of ovarian cancer mortality in a prospective cohort of postmenopausal women. Cancer Epidemiol Biomarkers Prev 2002;11:822–8.
    OpenUrlAbstract/FREE Full Text
  4. ↵
    Kjaerbye-Thygesen A, Frederiksen K, Hogdall EV, et al. Smoking and overweight: negative prognostic factors in stage III epithelial ovarian cancer. Cancer Epidemiol Biomarkers Prev 2006;15:798–803.
    OpenUrlAbstract/FREE Full Text
  5. ↵
    Zhang M, Xie X, Lee AH, Binns CW, Holman CDAJ. Body mass index in relation to ovarian cancer survival. Cancer Epidemiol Biomarkers Prev 2005;14:1307–10.
    OpenUrlAbstract/FREE Full Text
  6. ↵
    Pavelka JC, Brown RS, Karlan BY, et al. Effect of obesity on survival in epithelial ovarian cancer. Cancer 2006;107:1520–4.
    OpenUrlCrossRefPubMed
  7. ↵
    Schildkraut JM, Halabi S, Bastos E, Marchbanks PA, McDonald JA, Berchuck A. Prognostic factors in early-onset epithelial ovarian cancer: a population-based study. Obstet Gynecol 2000;95:119–27.
    OpenUrlCrossRefPubMed
  8. ↵
    McCann SE, Moysich KB, Mettlin C. Intakes of selected nutrients and food groups and risk of ovarian cancer. Nutr Cancer 2001;39:19–28.
    OpenUrlCrossRefPubMed
  9. Moysich KB, Mettlin C, Piver MS, Natarajan N, Menezes RJ, Swede H. Regular use of analgesic drugs and ovarian cancer risk. Cancer Epidemiol Biomarkers Prev 2001;10:903–6.
    OpenUrlAbstract/FREE Full Text
  10. Baker JA, Odunuga OO, Rodabaugh KJ, Reid ME, Menezes RJ, Moysich KB. Active and passive smoking and risk of ovarian cancer. Int J Gynecol Cancer 2006;16:211–8.
  11. ↵
    Beehler GP, Sekhon M, Baker JA, et al. Risk of ovarian cancer associated with BMI varies by menopausal status. J Nutr 2006;136:2881–6.
    OpenUrlAbstract/FREE Full Text
  12. Lew EA, Garfinkel L. Variations in mortality by weight among 750,000 men and women. J Chron Dis 1979;32:563–76.
    OpenUrlCrossRefPubMed
  13. ↵
    Wolfberg AJ, Montz FJ, Bristow RE. Role of obesity in the surgical management of advanced-stage ovarian cancer. J Reprod Med 2004;49:473–6.
    OpenUrlPubMed
  14. ↵
    Dupont WD, Plummer WD. PS power and sample size program available for free on the Internet. Control Clin Trials 1997;18:274.
PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 16 (3)
March 2007
Volume 16, Issue 3
  • Table of Contents
  • Table of Contents (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Usual Adult Body Mass Index Is Not Predictive of Ovarian Cancer Survival
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Usual Adult Body Mass Index Is Not Predictive of Ovarian Cancer Survival
Kirsten B. Moysich, Julie A. Baker, Ravi J. Menezes, Vijayvel Jayaprakash, Kerry J. Rodabaugh, Kunle Odunsi, Gregory P. Beehler, Susan E. McCann and Jeannine A. Villella
Cancer Epidemiol Biomarkers Prev March 1 2007 (16) (3) 626-628; DOI: 10.1158/1055-9965.EPI-06-1052

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Usual Adult Body Mass Index Is Not Predictive of Ovarian Cancer Survival
Kirsten B. Moysich, Julie A. Baker, Ravi J. Menezes, Vijayvel Jayaprakash, Kerry J. Rodabaugh, Kunle Odunsi, Gregory P. Beehler, Susan E. McCann and Jeannine A. Villella
Cancer Epidemiol Biomarkers Prev March 1 2007 (16) (3) 626-628; DOI: 10.1158/1055-9965.EPI-06-1052
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Diet Quality and Ovarian Cancer Survival
  • PDE5 inhibitors use and precursors of colorectal cancer
  • Association between serum iron biomarkers and breast cancer
Show more Null Results in Brief
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement