Evidence map›Paper›PMID 32970194›Full record

ArticleAnnals of hematology2020

Validation and comparison of prognostic values of GNRI, PNI, and CONUT in newly diagnosed diffuse large B cell lymphoma.

Toshihiro Matsukawa, Keito Suto, Minoru Kanaya, Koh Izumiyama, Koichiro Minauchi, Shota Yoshida, Hisashi Oda, Takuto Miyagishima, Akio Mori, Shuichi Ota and 3 more

Abstract readComparative StudyMulticenter StudyValidation Study
PubMed Publisher
In one paragraph

Article in Annals of hematology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 8 pooled it
–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

38 citing papers in PubMed, 8 syntheses or guidelines pooled it.

  1. Predictive value of prognostic nutritional index as prognostic biomarkers in patients with lymphoma: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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  4. Prognostic value of geriatric nutritional risk index in patients with diffuse large B-cell lymphoma: a meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
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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

13 authors.

Toshihiro MatsukawaDepartment of Internal Medicine/Hematology, Kushiro Rosai Hospital, 13-23 Nakazono-Cho, Kushiro, 085-8533, Japan. t-matsukawa@hokkaido.med.or.jp.ORCID http://orcid.org/0000-0003-2371-3778
Keito SutoDepartment of Internal Medicine/Hematology, Kushiro Rosai Hospital, 13-23 Nakazono-Cho, Kushiro, 085-8533, Japan.
Minoru KanayaBlood Disorders Center, Aiiku Hospital, Sapporo, Japan.
Koh IzumiyamaBlood Disorders Center, Aiiku Hospital, Sapporo, Japan.
Koichiro MinauchiDepartment of Hematology, Sapporo Hokuyu Hospital, Sapporo, Japan.
Shota YoshidaDepartment of Internal Medicine/Hematology, Kushiro Rosai Hospital, 13-23 Nakazono-Cho, Kushiro, 085-8533, Japan.
Hisashi OdaDepartment of Internal Medicine/Hematology, Kushiro Rosai Hospital, 13-23 Nakazono-Cho, Kushiro, 085-8533, Japan.
Takuto MiyagishimaDepartment of Internal Medicine/Hematology, Kushiro Rosai Hospital, 13-23 Nakazono-Cho, Kushiro, 085-8533, Japan.
Akio MoriBlood Disorders Center, Aiiku Hospital, Sapporo, Japan.
Shuichi OtaDepartment of Hematology, Sapporo Hokuyu Hospital, Sapporo, Japan.
Daigo HashimotoDepartment of Hematology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
Takanori TeshimaDepartment of Hematology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
North Japan Hematology Study Group (NJHSG)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffuse large B cell lymphoma (DLBCL) is the most common type of aggressive non-Hodgkin lymphoma. Emerging evidence indicates that poor nutritional status determined with nutritional indices such as geriatric nutritional risk index (GNRI), prognostic nutritional index (PNI), and controlling nutritional status score (CONUT) was associated with poor prognosis of DLBCL. We conducted this multicenter retrospective study to validate and compare prognostic values of the three indices in 615 newly diagnosed DLBCL patients. The overall survival (OS) in patients with poor nutritional status determined with each of these nutritional indices were significantly inferior compared with that in those without nutritional risks (5-year OS in patients with GNRI < 95.7 and GNRI ≥ 95.7 were 56.4% and 83.5%, P < 0.001; PNI < 42.4 and PNI ≥ 42.4 were 56.1% and 81.0%, P < 0.001; CONUT > 4 and CONUT ≤ 4 were 53.1% and 77.1%, P < 0.001). GNRI and CONUT were independent prognostic predictors for OS (GNRI < 95.7, hazard ratio [HR] 1.83, 95% confidence interval [CI] 1.22-2.74, P = 0.0032; CONUT > 4, HR 1.53, 95% CI 1.05-2.23, P = 0.028) after multivariate analyses. Nutritional status determined with GNRI affected OS more strongly in the patients with nongerminal center B cell-like (nonGCB) DLBCL compared with that in those with GCB-type DLBCL. In conclusion, baseline poor nutritional status determined based on GNRI or CONUT was an independent risk factor of newly diagnosed DLBCL, and GNRI was also useful as an independent prognostic factor for patients with nonGCB-type DLBCL.

Indexed as

Nutrition AssessmentAdultAgedAged, 80 and overFemaleGeriatric AssessmentHumansLymphoma, Large B-Cell, DiffuseMaleMiddle AgedPrognosisRetrospective StudiesYoung AdultControlling nutritional status scoreDiffuse large B cell lymphomaGeriatric nutritional risk indexNutritionPrognostic nutritional index

Identifiers

PMID32970194

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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.