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Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side.

Publication ,  Conference
Furchtgott, L; Swanson, D; Hayete, B; Khalil, I; Wuest, D; Rich, K; Nixon, AB; Niedzwiecki, D; Meyerhardt, JA; O'Reilly, EM; Ou, F-S ...
Published in: Journal of Clinical Oncology
May 20, 2017

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 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 side (L vs R) stratum-specific models to examine differences in drivers of disease in those strata. Results: 1 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 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 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 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.

Duke Scholars

Published In

Journal of Clinical Oncology

DOI

EISSN

1527-7755

ISSN

0732-183X

Publication Date

May 20, 2017

Volume

35

Issue

15_suppl

Start / End Page

3528 / 3528

Publisher

American Society of Clinical Oncology (ASCO)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Furchtgott, L., Swanson, D., Hayete, B., Khalil, I., Wuest, D., Rich, K., … Venook, A. P. (2017). Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side. In Journal of Clinical Oncology (Vol. 35, pp. 3528–3528). American Society of Clinical Oncology (ASCO). https://doi.org/10.1200/jco.2017.35.15_suppl.3528
Furchtgott, Leon, David Swanson, Boris Hayete, Iya Khalil, Diane Wuest, Kelly Rich, Andrew B. Nixon, et al. “Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side.” In Journal of Clinical Oncology, 35:3528–3528. American Society of Clinical Oncology (ASCO), 2017. https://doi.org/10.1200/jco.2017.35.15_suppl.3528.
Furchtgott L, Swanson D, Hayete B, Khalil I, Wuest D, Rich K, et al. Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side. In: Journal of Clinical Oncology. American Society of Clinical Oncology (ASCO); 2017. p. 3528–3528.
Furchtgott, Leon, et al. “Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side.Journal of Clinical Oncology, vol. 35, no. 15_suppl, American Society of Clinical Oncology (ASCO), 2017, pp. 3528–3528. Crossref, doi:10.1200/jco.2017.35.15_suppl.3528.
Furchtgott L, Swanson D, Hayete B, Khalil I, Wuest D, Rich K, Nixon AB, Niedzwiecki D, Meyerhardt JA, O’Reilly EM, Ou F-S, Lenz H-J, Innocenti F, Venook AP. Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side. Journal of Clinical Oncology. American Society of Clinical Oncology (ASCO); 2017. p. 3528–3528.

Published In

Journal of Clinical Oncology

DOI

EISSN

1527-7755

ISSN

0732-183X

Publication Date

May 20, 2017

Volume

35

Issue

15_suppl

Start / End Page

3528 / 3528

Publisher

American Society of Clinical Oncology (ASCO)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
  • 1103 Clinical Sciences