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Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer

Authors
 Lujia Chen  ;  Ying Wang  ;  Chunhui Cai  ;  Ying Ding  ;  Rim S Kim  ;  Corey Lipchik  ;  Patrick G Gavin  ;  Greg Yothers  ;  Carmen J Allegra  ;  Nicholas J Petrelli  ;  Jennifer Marie Suga  ;  Judith O Hopkins  ;  Naoyuki G Saito  ;  Terry Evans  ;  Srinivas Jujjavarapu  ;  Norman Wolmark  ;  Peter C Lucas  ;  Soonmyung Paik  ;  Min Sun  ;  Katherine L Pogue-Geile  ;  Xinghua Lu 
Citation
 JOURNAL OF CLINICAL ONCOLOGY, Vol.42(13) : 1520-1530, 2024-05 
Journal Title
JOURNAL OF CLINICAL ONCOLOGY
ISSN
 0732-183X 
Issue Date
2024-05
MeSH
Adult ; Aged ; Antineoplastic Combined Chemotherapy Protocols* / therapeutic use ; Chemotherapy, Adjuvant ; Clinical Trials, Phase III as Topic ; Colonic Neoplasms* / drug therapy ; Colonic Neoplasms* / mortality ; Colonic Neoplasms* / pathology ; Female ; Fluorouracil* / administration & dosage ; Fluorouracil* / therapeutic use ; Humans ; Leucovorin* / administration & dosage ; Leucovorin* / therapeutic use ; Machine Learning* ; Male ; Middle Aged ; Neoplasm Staging ; Organoplatinum Compounds / administration & dosage ; Organoplatinum Compounds / therapeutic use ; Oxaliplatin* / administration & dosage ; Oxaliplatin* / therapeutic use
Abstract
Purpose: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients who benefit from oxaliplatin would maximize efficacy and minimize unnecessary adverse side effects.

Methods: We trained a new machine learning model, referred to as the colon oxaliplatin signature (COLOXIS) model, for predicting response to oxaliplatin-containing regimens. We examined whether COLOXIS was predictive of oxaliplatin benefits in the CC adjuvant setting among 1,065 patients treated with 5-fluorouracil plus leucovorin (FULV; n = 421) or FULV + oxaliplatin (FOLFOX; n = 644) from NSABP C-07 and C-08 phase III trials. The COLOXIS model dichotomizes patients into COLOXIS+ (oxaliplatin responder) and COLOXIS- (nonresponder) groups. Eight-year recurrence-free survival was used to evaluate oxaliplatin benefits within each of the groups, and the predictive value of the COLOXIS model was assessed using the P value associated with the interaction term (int P) between the model prediction and the treatment effect.

Results: Among 1,065 patients, 526 were predicted as COLOXIS+ and 539 as COLOXIS-. The COLOXIS+ prediction was associated with prognosis for FULV-treated patients (hazard ratio [HR], 1.52 [95% CI, 1.07 to 2.15]; P = .017). The model was predictive of oxaliplatin benefits: COLOXIS+ patients benefited from oxaliplatin (HR, 0.65 [95% CI, 0.48 to 0.89]; P = .0065; int P = .03), but COLOXIS- patients did not (COLOXIS- HR, 1.08 [95% CI, 0.77 to 1.52]; P = .65).

Conclusion: The COLOXIS model is predictive of oxaliplatin benefits in the CC adjuvant setting. The results provide evidence supporting a change in CC adjuvant therapy: reserve oxaliplatin only for COLOXIS+ patients, but further investigation is warranted.

Trial registration: ClinicalTrials.gov NCT00096278 NCT00004931.
Full Text
https://ascopubs.org/doi/10.1200/JCO.23.01080
DOI
10.1200/JCO.23.01080
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers
Yonsei Authors
Paik, Soon Myung(백순명) ORCID logo https://orcid.org/0000-0001-9688-6480
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/201695
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