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Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer

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dc.contributor.author백순명-
dc.date.accessioned2025-02-03T08:28:09Z-
dc.date.available2025-02-03T08:28:09Z-
dc.date.issued2024-05-
dc.identifier.issn0732-183X-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/201695-
dc.description.abstractPurpose: 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.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherAmerican Society of Clinical Oncology-
dc.relation.isPartOfJOURNAL OF CLINICAL ONCOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHAntineoplastic Combined Chemotherapy Protocols* / therapeutic use-
dc.subject.MESHChemotherapy, Adjuvant-
dc.subject.MESHClinical Trials, Phase III as Topic-
dc.subject.MESHColonic Neoplasms* / drug therapy-
dc.subject.MESHColonic Neoplasms* / mortality-
dc.subject.MESHColonic Neoplasms* / pathology-
dc.subject.MESHFemale-
dc.subject.MESHFluorouracil* / administration & dosage-
dc.subject.MESHFluorouracil* / therapeutic use-
dc.subject.MESHHumans-
dc.subject.MESHLeucovorin* / administration & dosage-
dc.subject.MESHLeucovorin* / therapeutic use-
dc.subject.MESHMachine Learning*-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHNeoplasm Staging-
dc.subject.MESHOrganoplatinum Compounds / administration & dosage-
dc.subject.MESHOrganoplatinum Compounds / therapeutic use-
dc.subject.MESHOxaliplatin* / administration & dosage-
dc.subject.MESHOxaliplatin* / therapeutic use-
dc.titleMachine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentBioMedical Science Institute (의생명과학부)-
dc.contributor.googleauthorLujia Chen-
dc.contributor.googleauthorYing Wang-
dc.contributor.googleauthorChunhui Cai-
dc.contributor.googleauthorYing Ding-
dc.contributor.googleauthorRim S Kim-
dc.contributor.googleauthorCorey Lipchik-
dc.contributor.googleauthorPatrick G Gavin-
dc.contributor.googleauthorGreg Yothers-
dc.contributor.googleauthorCarmen J Allegra-
dc.contributor.googleauthorNicholas J Petrelli-
dc.contributor.googleauthorJennifer Marie Suga-
dc.contributor.googleauthorJudith O Hopkins-
dc.contributor.googleauthorNaoyuki G Saito-
dc.contributor.googleauthorTerry Evans-
dc.contributor.googleauthorSrinivas Jujjavarapu-
dc.contributor.googleauthorNorman Wolmark-
dc.contributor.googleauthorPeter C Lucas-
dc.contributor.googleauthorSoonmyung Paik-
dc.contributor.googleauthorMin Sun-
dc.contributor.googleauthorKatherine L Pogue-Geile-
dc.contributor.googleauthorXinghua Lu-
dc.identifier.doi10.1200/JCO.23.01080-
dc.contributor.localIdA01823-
dc.relation.journalcodeJ01331-
dc.identifier.eissn1527-7755-
dc.identifier.pmid38315963-
dc.identifier.urlhttps://ascopubs.org/doi/10.1200/JCO.23.01080-
dc.contributor.alternativeNamePaik, Soon Myung-
dc.contributor.affiliatedAuthor백순명-
dc.citation.volume42-
dc.citation.number13-
dc.citation.startPage1520-
dc.citation.endPage1530-
dc.identifier.bibliographicCitationJOURNAL OF CLINICAL ONCOLOGY, Vol.42(13) : 1520-1530, 2024-05-
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers

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