Comparing survival of older ovarian cancer patients treated with neoadjuvant chemotherapy versus primary cytoreductive surgery: Reducing bias through machine learning.
Gynecol Oncol
; 186: 9-16, 2024 07.
Article
in En
| MEDLINE
| ID: mdl-38554626
ABSTRACT
OBJECTIVE:
To develop and evaluate a multidimensional comorbidity index (MCI) that identifies ovarian cancer patients at risk of early mortality more accurately than the Charlson Comorbidity Index (CCI) for use in health services research.METHODS:
We utilized SEER-Medicare data to identify patients with stage IIIC and IV ovarian cancer, diagnosed in 2010-2015. We employed partial least squares regression, a supervised machine learning algorithm, to develop the MCI by extracting latent factors that optimally captured the variation in health insurance claims made in the year preceding cancer diagnosis, and 1-year mortality. We assessed the discrimination and calibration of the MCI for 1-year mortality and compared its performance to the commonly-used CCI. Finally, we evaluated the MCI's ability to reduce confounding in the association of neoadjuvant chemotherapy (NACT) and all-cause mortality.RESULTS:
We included 4723 patients in the development cohort and 933 in the validation cohort. The MCI demonstrated good discrimination for 1-year mortality (c-index 0.75, 95% CI 0.72-0.79), while the CCI had poor discrimination (c-index 0.59, 95% CI 0.56-0.63). Calibration plots showed better agreement between predicted and observed 1-year mortality risk for the MCI compared with CCI. When comparing all-cause mortality between NACT with primary cytoreductive surgery, NACT was associated with a higher hazard of death (HR 1.13, 95% CI 1.04-1.23) after controlling for tumor characteristics, demographic factors, and the CCI. However, when controlling for the MCI instead of the CCI, there was no longer a significant difference (HR 1.05, 95% CI 0.96-1.14).CONCLUSIONS:
The MCI outperformed the conventional CCI in predicting 1-year mortality, and reducing confounding due to differences in baseline health status in comparative effectiveness analysis of NACT versus primary surgery.Key words
Full text:
1
Database:
MEDLINE
Main subject:
Ovarian Neoplasms
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SEER Program
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Neoadjuvant Therapy
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Cytoreduction Surgical Procedures
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Machine Learning
Limits:
Aged
/
Aged80
/
Female
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Humans
Country/Region as subject:
America do norte
Language:
En
Year:
2024
Type:
Article