Evidence map›Paper›PMID 42682433›Full record

ArticleFrontiers in medicine2026

Early identification of high-risk myelosuppression subtypes in DLBCL patients undergoing R-CHOP chemotherapy.

Keyi Yang, Tianming Du, Guoxin Liu, Chen Li, Qiang Kang, Xinglong Zhang, Yang Hong, Na Sun, Wanqiang Ma, Fanli Kong and 1 more

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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11 authors.

Keyi Yang *Department of Pharmacy, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Tianming Du *College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
Guoxin Liu *The 967th Hospital of PLA Joint Logistics Support Force, Dalian, China.
Chen LiCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
Qiang KangDepartment of Radiology, Xing'an League People's Hospital of Inner Mongolia, Inner Mongolia, China.
Xinglong ZhangDepartment of Hematology, The Fourth Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Yang HongDepartment of Pharmacy, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Na SunDepartment of Pharmacy, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Wanqiang MaThe 967th Hospital of PLA Joint Logistics Support Force, Dalian, China.
Fanli KongDepartment of Pharmacy, Central Hospital of Dalian University of Technology, Dalian, China.
Guangjun FanDepartment of Pharmacy, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite prophylactic interventions, chemotherapy-related myelosuppression remains an important clinical concern in patients with diffuse large B-cell lymphoma (DLBCL) receiving R-CHOP. This study characterized its occurrence patterns, baseline predictors, temporal risk, and dynamic heterogeneity. Methods: We established an 8-year longitudinal cohort of patients with DLBCL who received standard-dose R-CHOP between 2016 and 2024. Endpoints included WHO-defined grade ≥1 and grade ≥3 myelosuppression and severe lineage-specific complications. Correlation analyses evaluated associations between baseline laboratory parameters and HGB-, NEUT-, PLT-, and WBC-related suppression. Multiple machine-learning models were developed for each endpoint and hematologic dimension. L2-regularized Cox proportional hazards models were used for time-to-event analyses, with supplementary time-dependent Cox analyses evaluating G-CSF exposure for NEUT-related endpoints. K-means clustering of longitudinal hematologic features was performed to identify dynamic subphenotypes. Results: Among 262 patients, advanced Lugano stage and the high-risk IPI subgroup were associated with several severe myelosuppression outcomes, while sex, infection status, and functional or anthropometric characteristics showed endpoint-specific associations. HCT, HGB, and RBC were negatively associated with HGB- and PLT-related myelosuppression and grade ≥3 NEUT-related myelosuppression, whereas RDW-CV and RDW-SD were positively associated with several severe outcomes. Models for HGB- and PLT-related endpoints achieved AUCs >0.80 for grade ≥1, grade ≥3, and corresponding severe-complication outcomes, whereas NEUT-related models showed lower discrimination. Baseline HCT was independently associated with lower hazards of grade ≥1 HGB-related myelosuppression (HR = 0.918, 95% CI 0.894-0.943), grade ≥3 HGB-related myelosuppression (HR = 0.910, 95% CI 0.882-0.940), and severe anemia (HR = 0.934, 95% CI 0.902-0.966). RDW-CV independently increased the hazards of grade ≥1 and grade ≥3 PLT-related myelosuppression, while baseline NEUT# reduced the hazard of grade ≥1 NEUT-related myelosuppression (HR = 0.835, 95% CI 0.760-0.918; FDR-adjusted Conclusion: R-CHOP-related myelosuppression is heterogeneous in occurrence, temporal evolution, and recovery. Baseline clinical and laboratory features may support early risk stratification, dynamic monitoring, and individualized supportive care.

Indexed as

chemotherapy-induced myelosuppressionDLBCLlongitudinal dynamicspredictive biomarkerssub-phenotyping

Identifiers

PMID42682433
PMCPMC13529567

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