Characteristics of Patients and Prognostic Factors Across Treatment Lines in Metastatic Colorectal Cancer: An Analysis From the Aide et Recherche en Cancérologie Digestive Database

J Jean-Baptiste Bachet A Aimery De Gramont (Institut Hospitalier Franco-Britannique, Levallois-Perret, France) M Morteza Raeisi (Statistical Unit, ARCAD Foundation, Paris, France) M Manel Rakez (Statistical Unit, ARCAD Foundation, Paris, France) R Richard M. Goldberg (Department of Hematology and Oncology, West Virginia University Cancer Institute, Morgantown) N Niall C. Tebbutt E Eric Van Cutsem (University Hospitals Gasthuisberg, Leuven, Belgium) D Daniel G. Haller (Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA) J J. Randolph Hecht (UCLA Jonsson Comprehensive Cancer Center, Santa Monica, CA) R Robert J. Mayer (School of Natural Sciences Department Chemie Technical University of Munich 85748 Garching Germany) S Stuart M. Lichtman (Wilmot Cancer Institute Geriatric Oncology Research Group, University of Rochester, Rochester, NY) A Al B. Benson (Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL) A Alberto F. Sobrero (IRCCS Azienda Ospedaliera Metropolitana - Ospedale Policlinico San Martino, Genova, Italy) J Josep Tabernero (Vall d’Hebron Hospital Campus, Barcelona) R Richard Adams J John R. Zalcberg (Monash University School of Public Health and Preventive Medicine and Department of Medical Oncology, Alfred Health, Melbourne, VIC, Australia) A Axel Grothey T Takayuki Yoshino (National Cancer Center Hospital East, Kashiwa, Japan) T Thierry André Q Qian Shi B Benoist Chibaudel (Department of Medical Oncology, Franco-British Hospital, Fondation Cognacq-Jay, Cancérologie Paris Ouest, Levallois-Perret, France)

Abstract

PURPOSE Several lines of treatment can be used sequentially in patients with metastatic colorectal cancer. We investigated the evolution of patient/tumor characteristics and their prognostic impact across treatment lines to develop an overall prognostic score (OPS). PATIENTS AND METHODS Individual patient data from 48 randomized trials were analyzed. The end point was overall survival (from random assignment to death). Missing data were imputed. The complete data set was then separated into construction (80%) and validation sets (20%). The Cox's model was used to define risk groups for survival using the OPS. The discrimination capability was assessed in each treatment-line via bootstrapping to obtain optimism-corrected calibration and discrimination C-indices. Internal validation was done in the validation set. RESULTS A total of 37,560 patients (26,974 in first-line [1L], 7,693 in second-line [2L], and 2,893 in third-line [3L]) were analyzed. Some clinical, biological, and molecular characteristics of patients/tumors included in therapeutic trials evolve over the lines. Seven independent prognostic variables were retained in the final multivariate model common to all lines: Eastern Cooperative Oncology Group performance status, hemoglobin, platelet count, WBC/absolute neutrophil count ratio, lactate dehydrogenase, alkaline phosphatase, and the number of metastatic sites. The OPS was used to define four patient subgroups with significantly different prognoses in 1L, 2L, and 3L, separately, with adequate C-indices: 0.65, 0.66, and 0.69 in the construction set and 0.65, 0.66, and 0.68 in the validation set, respectively. The OPS was not predictive, with 3L drugs ( v placebo) or subsequent line (2L/1L or 3L/2L) extending survival in all prognostic groups. CONCLUSION The same prognostic model using practical variables can be used before all treatment lines. The OPS could better stratify patients in future clinical trials and help to therapeutic decision in routine practice.

Article Details

Volume / Issue Vol. 43, Issue 18
Published June 20, 2025
Pages 2094-2106
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (21)

J

Jean-Baptiste Bachet

A

Aimery De Gramont

Institut Hospitalier Franco-Britannique, Levallois-Perret, France

M

Morteza Raeisi

Statistical Unit, ARCAD Foundation, Paris, France

M

Manel Rakez

Statistical Unit, ARCAD Foundation, Paris, France

R

Richard M. Goldberg

Department of Hematology and Oncology, West Virginia University Cancer Institute, Morgantown

N

Niall C. Tebbutt

E

Eric Van Cutsem

University Hospitals Gasthuisberg, Leuven, Belgium

D

Daniel G. Haller

Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA

J

J. Randolph Hecht

UCLA Jonsson Comprehensive Cancer Center, Santa Monica, CA

R

Robert J. Mayer

School of Natural Sciences Department Chemie Technical University of Munich 85748 Garching Germany

S

Stuart M. Lichtman

Wilmot Cancer Institute Geriatric Oncology Research Group, University of Rochester, Rochester, NY

A

Al B. Benson

Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL

A

Alberto F. Sobrero

IRCCS Azienda Ospedaliera Metropolitana - Ospedale Policlinico San Martino, Genova, Italy

J

Josep Tabernero

Vall d’Hebron Hospital Campus, Barcelona

R

Richard Adams

J

John R. Zalcberg

Monash University School of Public Health and Preventive Medicine and Department of Medical Oncology, Alfred Health, Melbourne, VIC, Australia

A

Axel Grothey

T

Takayuki Yoshino

National Cancer Center Hospital East, Kashiwa, Japan

T

Thierry André

Q

Qian Shi

B

Benoist Chibaudel

Department of Medical Oncology, Franco-British Hospital, Fondation Cognacq-Jay, Cancérologie Paris Ouest, Levallois-Perret, France