Predictors of quality of care and survival in a three-state cohort of locally advanced cervical cancer patients and development of a predictive model to identify women at risk of incomplete treatment. Issue 33 (August 2019)

• Record Type: Journal Article
• Authors: Schad, Michael D.; Moore, Joanna; Camacho, Fabian; Anderson, Roger T.; Cantrell, Leigh A.; Showalter, Timothy N.
• Other Names: Ding. Jianxun section editor.
• Is Part Of: Medicine. Volume 98:Issue 33(2019)
• Publication Date: 2019-08
• Subjects: brachytherapy -- cervical cancer -- disparities -- quality; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000016874
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: To expand our prior statewide analysis of care distribution for locally advanced cervical cancer in Virginia to include 2 more states and to develop a tool for predicting quality of care. Complete treatment was defined as receiving chemotherapy (CT), brachytherapy (BT), and external beam radiotherapy. State cancer registry databases yielded a three-state cohort of 3197 women diagnosed with locally advanced cervical cancer from 2000 to 2013. A logistic regression evaluated predictors for receipt of BT, CT, and high (2–3 modalities received) versus low (0–1 modalities received) quality care. A Cox proportional hazards models determined predictors of survival. Finally, a predictive model was developed and preliminarily validated using our cohort. Only 35.3% of the cohort received complete treatment and only 57.3% received BT. Significant predictors of lower odds of receiving high quality care varied by state but included: 66+ age at diagnosis as compared to 18 to 42, 42 to 53, or 53 to 66; cancer stage IVA as compared to IIIx, IIx, or IB2; public insurance with supplement as compared to private; treatment at a low volume facility; and closer distance quintiles to a high volume treatment center as compared to the furthest quintile. Significant predictors of worse survival varied by state but included: low quality score (0–1 modalities received); 2000 to 2004 or 2005 to 2009 year of diagnosis as compared to 2010 to 2013; 66+ age at diagnosis as compared to 18 to 42, 42 to 53, or 53 to 66; cancer stage IVA as compared to IIIx, IIx, or IB2; treatment at a low volume facility; and unmarried/unknown marital status as compared to married. Our treatment quality prediction tool included age, age 2, treatment at high volume facility, and cancer stage and demonstrated 78.2% sensitivity and a 62.9% specificity. Only 35.3% of patients received complete guidelines-concordant treatment. Additionally, in 2/3 states it appeared that BT usage may have decreased during the study period. Our predictive model may help identify patients/regions at risk of receiving low quality care to target interventions aimed at improving cervical cancer treatment quality and survival. Abstract : Supplemental Digital Content is available in the text