Evidence map›Paper›PMID 36387101›Full record

ArticleFrontiers in oncology2022

Predicting immunotherapy outcomes in patients with MSI tumors using NLR and CT global tumor volume.

Younes Belkouchi, Laetitia Nebot-Bral, Littisha Lawrance, Michele Kind, Clémence David, Samy Ammari, Paul-Henry Cournède, Hugues Talbot, Perrine Vuagnat, Cristina Smolenschi and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 21% of its field
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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Therapeutic targeting of mismatch repair-deficient cancers.Nature reviews. Clinical oncology · 2025
    Review
  3. Article
  4. Article
  5. 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

14 authors at 6 institutions in 1 country.

Younes BelkouchiLaboratoire d'Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS), UMR 1281, Université Paris-Saclay, Inserm, CNRS, CEA, Villejuif, France.
Laetitia Nebot-BralUMR9019 - CNRS, Intégrité du Génome et Cancer, Université Paris-Saclay, Gustave Roussy, Villejuif, France.
Littisha LawranceLaboratoire d'Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS), UMR 1281, Université Paris-Saclay, Inserm, CNRS, CEA, Villejuif, France.
Michele KindDépartement d'Imagerie Médicale, Institut Bergonié, Bordeaux, France.
Clémence DavidLaboratoire d'Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS), UMR 1281, Université Paris-Saclay, Inserm, CNRS, CEA, Villejuif, France.
Samy AmmariLaboratoire d'Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS), UMR 1281, Université Paris-Saclay, Inserm, CNRS, CEA, Villejuif, France.
Paul-Henry CournèdeMathématiques et Informatique pour la Complexité et les Systèmes (MICS), CentraleSupélec, Université Paris-Saclay, Gif-Sur-Yvette, France.
Hugues TalbotOPtimisation Imagerie et Santé (OPIS), Inria, CentraleSupélec, Université Paris-Saclay, Gif-Sur-Yvette, France.
Perrine VuagnatDépartement d'Innovation Thérapeutique et d'Essais Précoces (DITEP), Gustave Roussy, Université Paris Saclay, Villejuif, France.
Cristina SmolenschiDépartement d'Innovation Thérapeutique et d'Essais Précoces (DITEP), Gustave Roussy, Université Paris Saclay, Villejuif, France.
Patricia L KannoucheUMR9019 - CNRS, Intégrité du Génome et Cancer, Université Paris-Saclay, Gustave Roussy, Villejuif, France.
Nathalie ChaputUMR9019 - CNRS, Intégrité du Génome et Cancer, Université Paris-Saclay, Gustave Roussy, Villejuif, France.
Nathalie LassauLaboratoire d'Imagerie Biomédicale Multimodale Paris-Saclay (BIOMAPS), UMR 1281, Université Paris-Saclay, Inserm, CNRS, CEA, Villejuif, France.
Antoine HollebecqueDépartement d'Innovation Thérapeutique et d'Essais Précoces (DITEP), Gustave Roussy, Université Paris Saclay, Villejuif, France.
Université Paris-Saclay · FRCEA Paris-Saclay · FRInstitut Gustave Roussy · FRCentraleSupélec · FRCentre National de la Recherche Scientifique · FRInstitut Bergonié · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Anti-PD-(L)1 treatment is indicated for patients with mismatch repair-deficient (MMRD) tumors, regardless of tumor origin. However, the response rate is highly heterogeneous across MMRD tumors. The objective of the study is to find a score that predicts anti-PD-(L)1 response in patients with MMRD tumors. Methods: Sixty-one patients with various origin of MMRD tumors and treated with anti-PD-(L)1 were retrospectively included in this study. An expert radiologist annotated all tumors present at the baseline and first evaluation CT-scans for all the patients by circumscribing them on their largest axial axis (single slice), allowing us to compute an approximation of their tumor volume. In total, 2120 lesions were annotated, which led to the computation of the total tumor volume for each patient. The RECIST sum of target lesions' diameters and neutrophile-to-lymphocyte (NLR) were also reported at both examinations. These parameters were determined at baseline and first evaluation and the variation between the first evaluation and baseline was calculated, to determine a comprehensive score for overall survival (OS) and progression-free survival (PFS). Results: Total tumor volume at baseline was found to be significantly correlated to the OS (p-value: 0.005) and to the PFS (p-value:<0.001). The variation of the RECIST sum of target lesions' diameters, total tumor volume and NLR were found to be significantly associated to the OS (p-values:<0.001, 0.006,<0.001 respectively) and to the PFS (<0.001,<0.001, 0.007 respectively). The concordance score combining total tumor volume and NLR variation was better at stratifying patients compared to the tumor volume or NLR taken individually according to the OS (pairwise log-rank test p-values: 0.033,<0.001, 0.002) and PFS (pairwise log-rank test p-values: 0.041,<0.001, 0.003). Conclusion: Total tumor volume appears to be a prognostic biomarker of anti-PD-(L)1 response to immunotherapy in metastatic patients with MMRD tumors. Combining tumor volume and NLR with a simple concordance score stratifies patients well according to their survival and offers a good predictive measure of response to immunotherapy.

Indexed as

anti-PD1anti PDL1biomarkerCT scanimmunotherapymismatch repair (MMR) deficiencyneutrophile-to-lymphocyte ratio (NLR)tumor volume

Identifiers

PMID36387101
PMCPMC9641225
OpenAlexW4307372680

What OpenQuestion holds

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Registered trials

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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.