Chemotherapy predictors and a time-dependent chemotherapy effect in metastatic esophageal cancer.

Chemotherapy Esophageal cancer Metastatic Predictors Survival

Journal

World journal of gastrointestinal oncology
ISSN: 1948-5204
Titre abrégé: World J Gastrointest Oncol
Pays: China
ID NLM: 101532470

Informations de publication

Date de publication:
15 Feb 2022
Historique:
received: 16 03 2021
revised: 01 07 2021
accepted: 25 12 2022
entrez: 23 3 2022
pubmed: 24 3 2022
medline: 24 3 2022
Statut: ppublish

Résumé

Chemotherapy has long been shown to confer a survival benefit in patients with metastatic esophageal cancer. However, not all patients with metastatic disease receive chemotherapy. To evaluate a large cancer database of metastatic esophageal cancer cases to identify predictors of receipt to chemotherapy and survival. We interrogated the National Cancer Database (NCDB) between 2004-2015 and included patients with M1 disease who had received or did not receive chemotherapy. A logistic regression model was used to examine the associations between chemotherapy and potential confounders and a Cox proportional hazards model was employed to examine the effect of chemotherapy on overall survival (OS). Propensity score analyses were further performed to balance measurable confounders between patients treated with and without chemotherapy. A total of 29182 patients met criteria for inclusion in this analysis, with 21911 (75%) receiving chemotherapy and 7271 (25%) not receiving chemotherapy. The median follow-up was 69.45 mo. The median OS for patients receiving chemotherapy was 9.53 mo (9.33-9.72) In this large, retrospective NCDB analysis, we identified several socioeconomic and clinicopathologic predictors for receiving chemotherapy and OS in patients with metastatic esophageal cancer. The benefit of chemotherapy on OS is time-dependent and favors early initiation. Focused outreach in lower income and underinsured patients is critical as receipt of chemotherapy is associated with improved OS.

Sections du résumé

BACKGROUND BACKGROUND
Chemotherapy has long been shown to confer a survival benefit in patients with metastatic esophageal cancer. However, not all patients with metastatic disease receive chemotherapy.
AIM OBJECTIVE
To evaluate a large cancer database of metastatic esophageal cancer cases to identify predictors of receipt to chemotherapy and survival.
METHODS METHODS
We interrogated the National Cancer Database (NCDB) between 2004-2015 and included patients with M1 disease who had received or did not receive chemotherapy. A logistic regression model was used to examine the associations between chemotherapy and potential confounders and a Cox proportional hazards model was employed to examine the effect of chemotherapy on overall survival (OS). Propensity score analyses were further performed to balance measurable confounders between patients treated with and without chemotherapy.
RESULTS RESULTS
A total of 29182 patients met criteria for inclusion in this analysis, with 21911 (75%) receiving chemotherapy and 7271 (25%) not receiving chemotherapy. The median follow-up was 69.45 mo. The median OS for patients receiving chemotherapy was 9.53 mo (9.33-9.72)
CONCLUSION CONCLUSIONS
In this large, retrospective NCDB analysis, we identified several socioeconomic and clinicopathologic predictors for receiving chemotherapy and OS in patients with metastatic esophageal cancer. The benefit of chemotherapy on OS is time-dependent and favors early initiation. Focused outreach in lower income and underinsured patients is critical as receipt of chemotherapy is associated with improved OS.

Identifiants

pubmed: 35317320
doi: 10.4251/wjgo.v14.i2.511
pmc: PMC8919005
doi:

Types de publication

Journal Article

Langues

eng

Pagination

511-524

Informations de copyright

©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflict-of-interest statement: No conflict of interest.

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Auteurs

Lauren Midthun (L)

Department of Medicine, Division of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Sungjin Kim (S)

Biostatistics and Bioinformatics Research Center, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States.

Andrew Hendifar (A)

Samuel Oschin Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Arsen Osipov (A)

Department of Medicine, Division of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Samuel J Klempner (SJ)

Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Brigham and Women's Hospital/Harvard Medical School, Boston, MA 02114, United States.

Joseph Chao (J)

Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, United States.

May Cho (M)

Division of Hematology and Oncology, Department of Medicine, University of California, Irvine, CA 92697, United States.

Michelle Guan (M)

Department of Medicine, Division of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Veronica R Placencio-Hickok (VR)

Department of Medicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States.

Alexandra Gangi (A)

Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Miguel Burch (M)

Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

De-Chen Lin (DC)

Department of Medicine, Division of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Kevin Waters (K)

Department of Pathology and Laboratory Medicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States.

Katelyn Atkins (K)

Department of Radiation Oncology, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States.

Mitchell Kamrava (M)

Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.

Jun Gong (J)

Department of Medicine, Division of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States. jun.gong@cshs.org.

Classifications MeSH