The reliability and validity of lung cancer and melanoma clinical quality survival measures.

OBJECTIVE

To develop a risk adjustment approach and test reliability and validity for oncology survival measures.

DATA SOURCES AND STUDY SETTING

We used the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare data from 2010 to 2013, with mortality data through 2015.

STUDY DESIGN

We developed 2-year risk-standardized survival rates (RSSR) for melanoma, non-small cell lung cancer (NSCLC), and small cell lung cancer (SCLC). Patients were attributed to group practices based on the plurality of visits. We identified the risk-adjustment variables via bootstrap and calculated the RSSRs. Reliability was tested via three approaches: (1) signal-to-noise ratio (SNR) reliability, (2) split-half, and (3) test-retest using bootstrap. We tested known group validity by stage at diagnosis using Cohen's d.

DATA COLLECTION/EXTRACTION METHODS: We selected all patients enrolled in Medicare and linked to SEER during the measurement period with an incident first primary diagnosis of stage I-IV melanoma, NSCLC, or SCLC. We excluded patients with missing data on month and/or stage of diagnosis.

PRINCIPAL FINDINGS

Results are based on patients with melanoma (n = 4344); NSCLC (n = 16,080); and SCLC (n = 2807) diagnosed between 2012 and 2013. The median (interquartile range) for the RSSRs at the group practice-level were 0.89 (0.83-0.87) for melanoma, 0.37 (0.30-0.43) for NSCLC, and 0.19 (0.11-0.25) for SCLC. C-statistics for the models ranged from 0.725 to 0.825. The reliability varied by approach with median SNR 0.20, 0.25, and 0.13; median test-retest 0.59, 0.57, and 0.56; median split-half reliability 0.21, 0.29, and 0.29 for melanoma, NSCLC, and SCLC, respectively. Cohen's d for stage I-IIIa and IIIb+ was 1.27, 0.86, 0.60 for melanoma, NSCLC, and SCLC, respectively.

CONCLUSIONS

Our results suggest that these cancer survival measures demonstrated adequate test-retest reliability and expected findings for the known-group validity analysis. If data limitations and feasibility challenges can be addressed, implementation of these quality measures may provide a survival metric used for oncology quality improvement efforts.