Evidence map›Paper›PMID 39570570›Full record

ArticleInternational journal of clinical pharmacy2025

Development of a robust predictive model for neutropenia after esophageal cancer chemotherapy using GLMMLasso.

Shuhei Sugaya, Masashi Uchida, Takaaki Suzuki, Eiryo Kawakami, Itsuko Ishii

Abstract read
In one paragraph

Article in International journal of clinical pharmacy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shuhei SugayaDivision of Pharmacy, Chiba University Hospital, Chiba, Japan.
Masashi UchidaDivision of Pharmacy, Chiba University Hospital, Chiba, Japan. masac-u@chiba-u.jp.ORCID http://orcid.org/0000-0002-3171-9208
Takaaki SuzukiDivision of Pharmacy, Chiba University Hospital, Chiba, Japan.
Eiryo KawakamiAdvanced Data Science Project, RIKEN Information R&D and Strategy Headquarters, RIKEN, Yokohama, Kanagawa, Japan.
Itsuko IshiiDivision of Pharmacy, Chiba University Hospital, Chiba, Japan.

Funding

Japan Society for the Promotion of Science JPJSCCA20200006Moonshot Research and Development Program JPMJMS2025
6 · The paper itself

Abstract

backgroundNeutropenia can easily progress to febrile neutropenia and is a risk factor for life-threatening infections. Predicting and preventing severe neutropenia can help avoid such infections.

aimThis study aimed to develop an optimal model using advanced statistical methods to predict neutropenia after 5-fluorouracil/cisplatin chemotherapy for esophageal cancer and to create a nomogram for clinical application.

methodPatients who received 5-fluorouracil/cisplatin chemotherapy at Chiba University Hospital, Japan, between January 2011 and March 2021 were included. Clinical parameters were measured before the first, second, and third chemotherapy cycles and were randomly divided by patient into a training cohort (60%) and test cohort (40%). The predictive performance of Logistic, Stepwise, Lasso, and GLMMLasso models was evaluated by the area under the receiver-operating characteristic curve (AUC). A nomogram based on GLMMLasso was developed, and the accuracy of probabilistic predictions was evaluated by the Brier score.

resultsThe AUC for the first cycle of chemotherapy was 0.781 for GLMMLasso, 0.751 for Lasso, 0.697 for Stepwise, and 0.669 for Logistic. The respective AUCs for GLMMLasso in the second and third cycles were 0.704 and 0.900. The variables selected by GLMMLasso were cisplatin dose, 5-fluorouracil dose, use of leucovorin, sex, cholinesterase, and platelets. A nomogram predicting neutropenia was created based on each regression coefficient. The Brier score for the nomogram was 0.139.

conclusionWe have developed a predictive model with high performance using GLMMLasso. Our nomogram can represent risk visually and may facilitate the assessment of the probability of chemotherapy-induced severe neutropenia in clinical practice.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsEsophageal NeoplasmsNeutropeniaNomogramsAgedCisplatinFemaleFluorouracilHumansJapanMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk FactorsCisplatinFluorouracilEsophageal cancer chemotherapyGLMMLassoNeutropeniaNomogram

Identifiers

PMID39570570
PMCPMC12335393

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.