BACKGROUND: Conditional survival estimates account for time survived since diagnosis to provide prognostic information for long-term cancer survivors. For rectal cancer, stage-related treatment (eg, neoadjuvant radiotherapy) affects pathologic stage and therefore stage-associated survival estimates. OBJECTIVES: The aim of this study is to estimate conditional survival for patients who have rectal cancer and to develop an interactive calculator to use for individualized patient counseling. PATIENTS: Patients with rectal adenocarcinoma were identified by using the Surveillance Epidemiology and End Results registry (1988-2002, N = 22,610). DESIGN: Cox regression models were developed to determine adjusted survival estimates (years 1-10) and used to calculate 5-year adjusted conditional survival. Models were built separately for no radiotherapy, preoperative radiotherapy, postoperative radiotherapy, and patients with stage IV disease. Covariates included age, sex, race, tumor grade, and type of surgery. An Internet-based conditional survival calculator was developed. RESULTS: Radiotherapy was given to 42.6% of patients (14.1% preoperative, 28.4% postoperative). Significant improvements in 5-year conditional survival were observed for all stages, with the exception of stage I because of the initial high survival probability at diagnosis. Patients with advanced stage had the greatest improvements in conditional survival, with 5-year absolute increases of 33% (stage IIIC) and 54% (IV). Other factors associated with conditional survival included sequence of radiotherapy and surgery, age, race, and tumor grade. The Internet-based conditional survival calculator can be accessed at www.mdanderson.org/rectalcalculator. LIMITATIONS: The data source used does not include information on chemotherapy treatment, change in staging after neoadjuvant treatment, or patient comorbidities. CONCLUSION: Conditional survival estimates improve over 5 years in patients who have rectal cancer; the greatest improvements are observed among patients with advanced stage disease. The conditional survival calculator is an individualized decision support tool that informs patients, who must make non-treatment-related life decisions, and their clinicians planning follow-up and surveillance.
BACKGROUND: Conditional survival estimates account for time survived since diagnosis to provide prognostic information for long-term cancer survivors. For rectal cancer, stage-related treatment (eg, neoadjuvant radiotherapy) affects pathologic stage and therefore stage-associated survival estimates. OBJECTIVES: The aim of this study is to estimate conditional survival for patients who have rectal cancer and to develop an interactive calculator to use for individualized patient counseling. PATIENTS: Patients with rectal adenocarcinoma were identified by using the Surveillance Epidemiology and End Results registry (1988-2002, N = 22,610). DESIGN:Cox regression models were developed to determine adjusted survival estimates (years 1-10) and used to calculate 5-year adjusted conditional survival. Models were built separately for no radiotherapy, preoperative radiotherapy, postoperative radiotherapy, and patients with stage IV disease. Covariates included age, sex, race, tumor grade, and type of surgery. An Internet-based conditional survival calculator was developed. RESULTS: Radiotherapy was given to 42.6% of patients (14.1% preoperative, 28.4% postoperative). Significant improvements in 5-year conditional survival were observed for all stages, with the exception of stage I because of the initial high survival probability at diagnosis. Patients with advanced stage had the greatest improvements in conditional survival, with 5-year absolute increases of 33% (stage IIIC) and 54% (IV). Other factors associated with conditional survival included sequence of radiotherapy and surgery, age, race, and tumor grade. The Internet-based conditional survival calculator can be accessed at www.mdanderson.org/rectalcalculator. LIMITATIONS: The data source used does not include information on chemotherapy treatment, change in staging after neoadjuvant treatment, or patient comorbidities. CONCLUSION: Conditional survival estimates improve over 5 years in patients who have rectal cancer; the greatest improvements are observed among patients with advanced stage disease. The conditional survival calculator is an individualized decision support tool that informs patients, who must make non-treatment-related life decisions, and their clinicians planning follow-up and surveillance.
Authors: E Kapiteijn; C A Marijnen; I D Nagtegaal; H Putter; W H Steup; T Wiggers; H J Rutten; L Pahlman; B Glimelius; J H van Krieken; J W Leer; C J van de Velde Journal: N Engl J Med Date: 2001-08-30 Impact factor: 91.245
Authors: Samuel J Wang; Rachel Emery; Clifton D Fuller; Jong-Sung Kim; Dean F Sittig; Charles R Thomas Journal: Gastric Cancer Date: 2007-09-26 Impact factor: 7.370
Authors: Mark S Roh; Linda H Colangelo; Michael J O'Connell; Greg Yothers; Melvin Deutsch; Carmen J Allegra; Morton S Kahlenberg; Luis Baez-Diaz; Carol S Ursiny; Nicholas J Petrelli; Norman Wolmark Journal: J Clin Oncol Date: 2009-09-21 Impact factor: 44.544
Authors: B Fisher; N Wolmark; H Rockette; C Redmond; M Deutsch; D L Wickerham; E R Fisher; R Caplan; J Jones; H Lerner Journal: J Natl Cancer Inst Date: 1988-03-02 Impact factor: 13.506
Authors: Hak-Mien Quah; Joanne F Chou; Mithat Gonen; Jinru Shia; Deborah Schrag; Leonard B Saltz; Karyn A Goodman; Bruce D Minsky; W Douglas Wong; Martin R Weiser Journal: Cancer Date: 2008-07-01 Impact factor: 6.860
Authors: Julia R Berian; Amanda Cuddy; Amanda B Francescatti; Linda O'Dwyer; Y Nancy You; Robert J Volk; George J Chang Journal: J Cancer Surviv Date: 2017-06-22 Impact factor: 4.442
Authors: Neha Vapiwala; Charles R Thomas; Surbhi Grover; Mei Ling Yap; Timur Mitin; Lawrence N Shulman; Mary K Gospodarowicz; John Longo; Daniel G Petereit; Ronald D Ennis; James A Hayman; Danielle Rodin; Jeffrey C Buchsbaum; Bhadrasain Vikram; May Abdel-Wahab; Alan H Epstein; Paul Okunieff; Joel Goldwein; Patrick Kupelian; Joanne B Weidhaas; Margaret A Tucker; John D Boice; Clifton David Fuller; Reid F Thompson; Andrew D Trister; Silvia C Formenti; Mary-Helen Barcellos-Hoff; Joshua Jones; Kavita V Dharmarajan; Anthony L Zietman; C Norman Coleman Journal: Int J Radiat Oncol Biol Phys Date: 2019-05-22 Impact factor: 7.038
Authors: Tarik Sammour; Andrew Macleod; Tim J Chittleborough; Raaj Chandra; Susan M Shedda; Ian A Hastie; Ian T Jones; Ian P Hayes Journal: Int J Colorectal Dis Date: 2016-03-16 Impact factor: 2.571