TY  - JOUR
AU  - Alexander, M
AU  - Wolfe, R
AU  - Ball, D
AU  - Conron, M
AU  - Stirling, RG
AU  - Solomon, B
AU  - MacManus, M
AU  - Officer, A
AU  - Karnam, S
AU  - Burbury, K
AU  - Evans, SM
Y2  - 2020/12/21
Y1  - 2017/08/22
SN  - 0007-0920
UR  - http://hdl.handle.net/11343/256477
AB  - INTRODUCTION: Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables. METHODS: Prospective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell's c-statistic for discrimination and Cox-Snell residuals for calibration) in two independent validation cohorts (hospital 2, n=479 and hospital 3, n=284). RESULTS: The derived Lung Cancer Prognostic Index (LCPI) included stage, histology, mutation status, performance status, weight loss, smoking history, respiratory comorbidity, sex, and age. Two-year overall survival rates according to LCPI in the derivation and two validation cohorts, respectively, were 84, 77, and 68% (LCPI 1: score⩽9); 61, 61, and 42% (LCPI 2: score 10-13); 33, 32, and 14% (LCPI 3: score 14-16); 7, 16, and 5% (LCPI 4: score ⩾15). Discrimination (c-statistic) was 0.74 for the derivation cohort, 0.72 and 0.71 for the two validation cohorts. CONCLUSIONS: The LCPI contributes additional prognostic information, which may be used to counsel patients, guide trial eligibility or design, or standardise mortality risk for epidemiological analyses.
LA  - English
PB  - NATURE PUBLISHING GROUP
T1  - Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer
DO  - 10.1038/bjc.2017.232
IS  - British Journal of Cancer
VL  - 117
IS  - 5
SP  - 744-751
L1  - /bitstream/handle/11343/256477/PMC5572183.pdf?sequence=1&isAllowed=y
ER  -