Diet- and Lifestyle‐Based Prediction Models to Estimate Cancer Recurrence and Death in Patients With Stage III Colon Cancer (CALGB 89803/Alliance)

Author:

Cheng En12ORCID,Ou Fang-Shu3ORCID,Ma Chao4ORCID,Spiegelman Donna56ORCID,Zhang Sui4ORCID,Zhou Xin56ORCID,Bainter Tiffany M.3,Saltz Leonard B.7ORCID,Niedzwiecki Donna8ORCID,Mayer Robert J.4,Whittom Renaud9,Hantel Alexander10,Benson Al11ORCID,Atienza Daniel12,Messino Michael13,Kindler Hedy14ORCID,Giovannucci Edward L.15ORCID,Van Blarigan Erin L.16ORCID,Brown Justin C.17ORCID,Ng Kimmie4ORCID,Gross Cary P.11819,Meyerhardt Jeffrey A.4,Fuchs Charles S.1202122ORCID

Affiliation:

1. Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT

2. Division of Research, Kaiser Permanente Northern California, Oakland, CA

3. Alliance Statistics and Data Management Center, Mayo Clinic, Rochester, MN

4. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA

5. Department of Biostatistics, Yale School of Public Health, New Haven, CT

6. Center on Methods for Implementation and Prevention Science, Yale School of Public Health, New Haven, CT

7. Memorial Sloan Kettering Cancer Center, New York, NY

8. Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC

9. Hôpital du Sacré-Coeur de Montréal, Montreal, Quebec, Canada

10. Loyola University, Stritch School of Medicine, Naperville, IL

11. Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL

12. Virginia Oncology Associates, Norfolk, VA

13. Messino Cancer Centers, Asheville, NC

14. University of Chicago, Chicago, IL

15. Department of Epidemiology, and Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA

16. Department of Epidemiology and Biostatistics, and Urology, University of California, San Francisco, CA

17. Cancer Metabolism Program, Pennington Biomedical Research Center, Baton Rouge, LA

18. Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT

19. Cancer Outcomes, Public Policy, and Effectiveness Research Center, Yale Cancer Center, New Haven, CT

20. Division of Hematology and Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT

21. Yale Cancer Center, Smilow Cancer Hospital, New Haven, CT

22. Hematology and Oncology Product Development, Genentech & Roche, South San Francisco, CA

Abstract

PURPOSE Current tools in predicting survival outcomes for patients with colon cancer predominantly rely on clinical and pathologic characteristics, but increasing evidence suggests that diet and lifestyle habits are associated with patient outcomes and should be considered to enhance model accuracy. METHODS Using an adjuvant chemotherapy trial for stage III colon cancer (CALGB 89803), we developed prediction models of disease-free survival (DFS) and overall survival by additionally incorporating self-reported nine diet and lifestyle factors. Both models were assessed by multivariable Cox proportional hazards regression and externally validated using another trial for stage III colon cancer (CALGB/SWOG 80702), and visual nomograms of prediction models were constructed accordingly. We also proposed three hypothetical scenarios for patients with (1) good-risk, (2) average-risk, and (3) poor-risk clinical and pathologic features, and estimated their predictive survival by considering clinical and pathologic features with or without adding self-reported diet and lifestyle factors. RESULTS Among 1,024 patients (median age 60.0 years, 43.8% female), we observed 394 DFS events and 311 deaths after median follow-up of 7.3 years. Adding self-reported diet and lifestyle factors to clinical and pathologic characteristics meaningfully improved performance of prediction models (c-index from 0.64 [95% CI, 0.62 to 0.67] to 0.69 [95% CI, 0.67 to 0.72] for DFS, and from 0.67 [95% CI, 0.64 to 0.70] to 0.71 [95% CI, 0.69 to 0.75] for overall survival). External validation also indicated good performance of discrimination and calibration. Adding most self-reported favorable diet and lifestyle exposures to multivariate modeling improved 5-year DFS of all patients and by 6.3% for good-risk, 21.4% for average-risk, and 42.6% for poor-risk clinical and pathologic features. CONCLUSION Diet and lifestyle factors further inform current recurrence and survival prediction models for patients with stage III colon cancer.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3