In:
Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 15_suppl ( 2017-05-20), p. 3528-3528
Abstract:
3528 Background: CALGB 80405 is a phase III clinical trial of FOLFOX and FOLFIRI w/ randomly assigned cetuximab or bevacizumab. Novel machine learning approaches to the study dataset provide valuable insights into CRC prognosis and management of CRC progression. Methods: Using a Monte Carlo Bayesian Generalized Linear Model analytical platform, we built an ensemble of models for overall survival (OS). We used 99 baseline and demographic variables, including 1904 patients w/ 1 o side and 949 w/ KRAS wild-type status. Building an ensemble of predictive models reduces risk of overfitting, estimates model uncertainty and identifies key variables by model consensus as measured by ensemble frequency (freq). We fit gender and 1 o side (L vs R) stratum-specific models to examine differences in drivers of disease in those strata. Results: 1 o side (avg Cox hazard ratio = 0.89, R side reference), ECOG performance status (1.30, reference level 0), AST concentration (1.01), peripheral neutrophil percentage (1.01) and local primary and abdominal site of disease indicators (1.22; 1.26) were key variables predictive of OS ( 〉 75% freq). In 1 o side stratum-specific models, urine protein level (1.61), treatment intent (0.75, nonpalliative as reference) and hemoglobin concentration (0.85) were more associated w/ L side progression (freq 〉 85% in L stratum model, 〈 20% in R), while liver and lung sites of disease (2.3; 1.09) were more associated w/ R side progression (freq 〉 65% in R stratum model, 〈 20% in L). Predictors of 1 o left-sidedness included age (avg log odds ratio = 0.02), hemoglobin (0.41), and abdominal (3.79) and liver (0.68) sites of disease. Modest differences in disease prognostic factors existed between genders: women more influenced by metastatic status, age, liver site of disease and creatinine level; men more influenced by urine protein level and prior diabetes. Conclusions: 1 o side plays a central role in potentially explaining both variation in OS and differences in drivers of OS. Availability of these measures at baseline enables better sense of disease course at initiation of treatment. Support: U10CA180821, U10CA180882, Eli Lilly & Co., Genentech, Pfizer Clinical trial information: NCT00265850.
Type of Medium:
Online Resource
ISSN:
0732-183X
,
1527-7755
DOI:
10.1200/JCO.2017.35.15_suppl.3528
Language:
English
Publisher:
American Society of Clinical Oncology (ASCO)
Publication Date:
2017
detail.hit.zdb_id:
2005181-5
