TY - JOUR
T1 - Ten-year conditional probability of survival for patients with ovarian cancer
T2 - A new metric tailored to Long-term survivors
AU - Kahn, Ryan
AU - Filippova, Olga
AU - Gordhandas, Sushmita
AU - An, Anjile
AU - Straubhar, Alli M
AU - Zivanovic, Oliver
AU - Gardner, Ginger J
AU - O'Cearbhaill, Roisin E
AU - Tew, William P
AU - Grisham, Rachel N
AU - Sonoda, Yukio
AU - Long Roche, Kara
AU - Abu-Rustum, Nadeem R
AU - Chi, Dennis S
N1 - Copyright © 2022 Elsevier Inc. All rights reserved.
PY - 2023/2
Y1 - 2023/2
N2 - OBJECTIVES: We assessed a conditional probability of survival (CPS) model to determine the probability of living 10 years after ovarian cancer diagnosis after having already survived 5 years.METHODS: We identified patients newly diagnosed with high-grade epithelial ovarian cancer from 1/1/2001-12/31/2009 and treated at our institution. Patients with <3 years follow-up were excluded. CPS was defined as the probability of surviving additional years (y) based on the condition a patient had already survived a given time (x): S(x + y)/S(x). Confidence intervals were estimated using a variation of Greenwood's formula.RESULTS: Of 916 patients meeting inclusion criteria, 473 (52%) were diagnosed from 2001 to 2005 and 443 (48%) from 2006 to 2009. Median age at diagnosis was 60 years (range, 25-95). The conventional 10-year OS rate for all patients was 29% (95% CI: 26%-32%)-75% (95% CI: 68%-82%) for stage I/II disease, 22% (95% CI: 19%-26%) for stage III, and 6.9% (95% CI: 3.9%-12%) for stage IV. For patients <65 years, the 10-year CPS for 5-year survivors was 65% (95% CI: 59%-70%); for those ≥65 years, it was 48% (95% CI: 38%-57%). For patients <65 years, the 10-year CPS for 5-year survivors by stage was: stage I/II, 89% (95% CI: 81%-94%); stage III, 58% (95% CI: 50%-66%); and stage IV, 26% (95% CI: 12%-42%). For patients ≥65 years, rates by stage were 78% (95% CI: 53%-91%), 42% (95% CI: 30%-53%), and 29% (95% CI: 7%-56%), respectively.CONCLUSIONS: For long-term survivors with high-grade epithelial ovarian cancer, CPS provides better prediction of survival than conventional methods.
AB - OBJECTIVES: We assessed a conditional probability of survival (CPS) model to determine the probability of living 10 years after ovarian cancer diagnosis after having already survived 5 years.METHODS: We identified patients newly diagnosed with high-grade epithelial ovarian cancer from 1/1/2001-12/31/2009 and treated at our institution. Patients with <3 years follow-up were excluded. CPS was defined as the probability of surviving additional years (y) based on the condition a patient had already survived a given time (x): S(x + y)/S(x). Confidence intervals were estimated using a variation of Greenwood's formula.RESULTS: Of 916 patients meeting inclusion criteria, 473 (52%) were diagnosed from 2001 to 2005 and 443 (48%) from 2006 to 2009. Median age at diagnosis was 60 years (range, 25-95). The conventional 10-year OS rate for all patients was 29% (95% CI: 26%-32%)-75% (95% CI: 68%-82%) for stage I/II disease, 22% (95% CI: 19%-26%) for stage III, and 6.9% (95% CI: 3.9%-12%) for stage IV. For patients <65 years, the 10-year CPS for 5-year survivors was 65% (95% CI: 59%-70%); for those ≥65 years, it was 48% (95% CI: 38%-57%). For patients <65 years, the 10-year CPS for 5-year survivors by stage was: stage I/II, 89% (95% CI: 81%-94%); stage III, 58% (95% CI: 50%-66%); and stage IV, 26% (95% CI: 12%-42%). For patients ≥65 years, rates by stage were 78% (95% CI: 53%-91%), 42% (95% CI: 30%-53%), and 29% (95% CI: 7%-56%), respectively.CONCLUSIONS: For long-term survivors with high-grade epithelial ovarian cancer, CPS provides better prediction of survival than conventional methods.
KW - Humans
KW - Female
KW - Adult
KW - Middle Aged
KW - Aged
KW - Aged, 80 and over
KW - Carcinoma, Ovarian Epithelial
KW - Neoplasm Staging
KW - Ovarian Neoplasms/pathology
KW - Probability
KW - Survivors
U2 - 10.1016/j.ygyno.2022.11.030
DO - 10.1016/j.ygyno.2022.11.030
M3 - Article
C2 - 36521353
SN - 0090-8258
VL - 169
SP - 85
EP - 90
JO - Gynecologic Oncology
JF - Gynecologic Oncology
ER -