Evidence map›Paper›PMID 38298193›Full record

ArticleFrontiers in immunology2024

Refining patient selection for next-generation immunotherapeutic early-phase clinical trials with a novel and externally validated prognostic nomogram.

Agnese Losurdo, Angelo Dipasquale, Laura Giordano, Pasquale Persico, Elena Lorenzi, Antonio Di Muzio, Chiara Barigazzi, James Korolewicz, Aman Mehan, Oreoluwa Mohammed and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Review
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 5 institutions in 3 countries.

Agnese Losurdo *Department of Biomedical Sciences, Humanitas University, Milan, Italy.
Angelo Dipasquale *Medical Oncology and Hematology Unit, IRCCS Humanitas Research Hospital, Humanitas Cancer Center, Milan, Italy.
Laura GiordanoBiostatistic Unit, IRCCS Humanitas Research Hospital, Humanitas Cancer Center, Milan, Italy.
Pasquale PersicoDepartment of Biomedical Sciences, Humanitas University, Milan, Italy.
Elena LorenziMedical Oncology and Hematology Unit, IRCCS Humanitas Research Hospital, Humanitas Cancer Center, Milan, Italy.
Antonio Di MuzioDepartment of Biomedical Sciences, Humanitas University, Milan, Italy.
Chiara BarigazziDepartment of Biomedical Sciences, Humanitas University, Milan, Italy.
James KorolewiczDivision of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, United Kingdom.
Aman MehanDivision of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, United Kingdom.
Oreoluwa MohammedDivision of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, United Kingdom.
Benhard ScheinerDivision of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria.
David J PinatoDivision of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, United Kingdom.
Armando Santoro *Department of Biomedical Sciences, Humanitas University, Milan, Italy.
Matteo Simonelli *Department of Biomedical Sciences, Humanitas University, Milan, Italy.
IRCCS Humanitas Research Hospital · ITHumanitas University · ITHammersmith Hospital · GBImperial College London · GBMedical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Identifying which patient may benefit from immunotherapeutic early-phase clinical trials is an unmet need in drug development. Among several proposed prognostic scores, none has been validated in patients receiving immunomodulating agents (IMAs)-based combinations. Patients and methods: We retrospectively collected data of 208 patients enrolled in early-phase clinical trials investigating IMAs at our Institution, correlating clinical and blood-based variables with overall survival (OS). A retrospective cohort of 50 patients treated with IMAs at Imperial College (Hammersmith Hospital, London, UK) was used for validation. Results: A total of 173 subjects were selected for analyses. Most frequent cancers included non-small cell lung cancer (26%), hepatocellular carcinoma (21.5%) and glioblastoma (13%). Multivariate analysis (MVA) revealed 3 factors to be independently associated with OS: line of treatment (second and third vs subsequent, HR 0.61, 95% CI 0.40-0.93, p 0.02), serum albumin as continuous variable (HR 0.57, 95% CI 0.36-0.91, p 0.02) and number of metastatic sites (<3 vs ≥3, HR 0.68, 95% CI 0.48-0.98, p 0.04). After splitting albumin value at the median (3.84 g/dL), a score system was capable of stratifying patients in 3 groups with significantly different OS (p<0.0001). Relationship with OS reproduced in the external cohort (p=0.008). Then, from these factors we built a nomogram. Conclusions: Prior treatment, serum albumin and number of metastatic sites are readily available prognostic traits in patients with advanced malignancies participating into immunotherapy early-phase trials. Combination of these factors can optimize patient selection at study enrollment, maximizing therapeutic intent.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsHumansImmunotherapyNomogramsPatient SelectionPrognosisRetrospective StudiesSerum AlbuminSerum Albuminearly-phases clinical trialsimmune-related adverse eventsimmunotherapynext-generations immunotherapiesprognostic scores

Identifiers

PMID38298193
PMCPMC10828843
OpenAlexW4390884515

What OpenQuestion holds

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LicenceCC BY
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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.