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An Interactive Tool for Individualized Estimation of Conditional Survival in Rectal Cancer

  • Colorectal Cancer
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

For rectal cancer patients who have already survived a period of time after diagnosis, survival probability changes and is more accurately depicted by conditional survival. The specific aim of this study was to develop an interactive tool for individualized estimation of changing prognosis for rectal cancer patients.

Methods

A multivariate Cox proportional hazards (CPH) survival model was constructed using data from rectal cancer patients diagnosed from 1994 to 2003 from the Surveillance, Epidemiology, and End Results (SEER) database. Age, race, sex, and stage were used as covariates in the survival prediction model. The primary outcome variable was overall survival conditional on having survived up to 5 years from diagnosis.

Results

Data from 42,830 rectal cancer patients met the inclusion criteria. The multivariate CPH model showed age, race, sex, and stage as significant independent predictors of survival. The survival prediction model demonstrated good calibration and discrimination, with a bootstrap-corrected concordance index of 0.75. A web-based prediction tool was built from this regression model that can compute individualized estimates of changing prognosis over time.

Conclusions

An interactive prediction modeling tool can estimate prognosis for rectal cancer patients who have already survived a period of time after diagnosis and treatment. Having more accurate prognostic information can empower both patients and clinicians to be able to make more appropriate decisions regarding follow-up, surveillance testing, and future treatment.

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Acknowledgment

Supported in part by the N.L. Tartar Research Fund.

Contributions

SJW, JYL, CDF, JKC, and CRT carried out the conception and design of this study. SJW and AWS coordinated the collection and assembly of data. SJW, AWS, CDF, and JKC participated in data analysis and interpretation. SJW, AWS, JYL, and CDF each helped draft the manuscript. SJW and CRT provided final approval of the manuscript.

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Authors and Affiliations

  1. Department of Radiation Medicine, Oregon Health and Science University, Portland, OR, USA

    Samuel J. Wang MD, PhD, Amanda R. Wissel BS & Charles R. Thomas Jr MD

  2. Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA

    Samuel J. Wang MD, PhD & Jayashree Kalpathy-Cramer PhD

  3. Department of Radiation Oncology, St. Joseph Hospital, Eureka, CA, USA

    Join Y. Luh MD

  4. Department of Radiation Oncology, University of Texas Health Science Center, San Antonio, TX, USA

    Join Y. Luh MD & C. David Fuller MD

Authors
  1. Samuel J. Wang MD, PhD
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  2. Amanda R. Wissel BS
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  3. Join Y. Luh MD
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  4. C. David Fuller MD
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  5. Jayashree Kalpathy-Cramer PhD
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  6. Charles R. Thomas Jr MD
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Corresponding author

Correspondence to Samuel J. Wang MD, PhD.

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Wang, S.J., Wissel, A.R., Luh, J.Y. et al. An Interactive Tool for Individualized Estimation of Conditional Survival in Rectal Cancer. Ann Surg Oncol 18, 1547–1552 (2011). https://doi.org/10.1245/s10434-010-1512-3

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  • DOI: https://doi.org/10.1245/s10434-010-1512-3

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