Short-term survival analysis of a risk-adjusted model for ovarian cancer care

Anjali Hari; Jenny Chang; Carolina Villanueva; Argyrios Ziogas; Veronica Vieira; Robert E Bristow

doi:10.1016/j.ygyno.2024.01.005

Short-term survival analysis of a risk-adjusted model for ovarian cancer care

Gynecol Oncol. 2024 Feb 2:184:123-131. doi: 10.1016/j.ygyno.2024.01.005. Online ahead of print.

Authors

Anjali Hari¹, Jenny Chang², Carolina Villanueva³, Argyrios Ziogas², Veronica Vieira⁴, Robert E Bristow⁵

Affiliations

¹ Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of California, Irvine School of Medicine, Orange, CA, USA; Chao Family Comprehensive Cancer Center, Orange, CA, USA. Electronic address: haria@hs.uci.edu.
² Department of Medicine, University of California, Irvine School of Medicine, Irvine, CA, USA.
³ Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, CA, USA.
⁴ Chao Family Comprehensive Cancer Center, Orange, CA, USA; Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, CA, USA.
⁵ Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of California, Irvine School of Medicine, Orange, CA, USA; Chao Family Comprehensive Cancer Center, Orange, CA, USA.

PMID: 38309029
DOI: 10.1016/j.ygyno.2024.01.005

Abstract

Objective: To quantify the impact on short-term ovarian cancer survival associated with treatment at high-performing hospitals using the observed-to-expected ratio (O/E) for adherence to ovarian cancer treatment guidelines as a risk-adjusted measure of hospital quality care.

Methods: This was a retrospective population-based study of stage I-IV invasive epithelial ovarian cancer reported to California Cancer Registry 1996-2017. A fit logistic regression model, risk-adjusted for patient and disease characteristics, was used to calculate O/E for each hospital stratified by hospital annual case volume. Cox proportional hazards model was used for survival analyses at 3, 6, 12, 24 months and stratified according to sociodemographic characteristics.

Results: The study population included 35,725 subjects treated at 443 hospitals: Low-O/E - 26.4% of cases; Intermediate-O/E - 55.5% of cases; and High-O/E - 18.1% of cases. Overall median survival by hospital category was: High-O/E = 72.5 months (95% CI = 68.6-78.6 months), Intermediate-O/E = 68.6 months (95% CI = 65.9-71.6 months), Low-O/E = 47.0 months (95% CI = 44.2-49.2 months). Initial treatment at a High-O/E hospital (HR = 1.00) was a statistically significant and independent predictor of improved short-term survival compared to Low-O/E hospitals at 3 months (HR = 1.46, 95% CI = 1.29-1.65), 6 months (HR = 1.35, 95% CI = 1.22-1.50), 12 months (HR = 1.27, 95% CI = 1.17-1.38), and 24 months (HR = 1.19, 95% CI = 1.11-1.27). Significant and independent associations between improved sort-term survival and High/O/E care were observed for Whites, Hispanics, Asian/Pacific Islanders (A/PI), across SES strata, and among all payer categories.

Conclusion: Ovarian cancer care at a High-O/E hospital is an independent predictor of improved outcome and the survival advantage is disproportionately weighted toward the short-term time horizon following diagnosis.

Keywords: High performing hospital (high O/E); Ovarian cancer; Short term survival.