Evidence map›Paper›PMID 37011230›Full record

ArticleThe oncologist2023

Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors.

Igor Stukalin, Vishal Navani, Mehul Gupta, Yibing Ruan, Devon J Boyne, Dylan E O'Sullivan, Daniel E Meyers, Siddhartha Goutam, Michael Sander, Benjamin W Ewanchuk and 6 more

Abstract read
In one paragraph

Article in The oncologist, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

16 authors.

Igor StukalinDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.ORCID 0000-0002-0943-8637
Vishal NavaniDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.ORCID 0000-0002-6795-009X
Mehul GuptaDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Yibing RuanDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Devon J BoyneDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Dylan E O'SullivanDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Daniel E MeyersDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Siddhartha GoutamDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Michael SanderDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Benjamin W EwanchukDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Darren R BrennerDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Aleksi SuoDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Winson Y CheungDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Daniel Y C HengDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Jose G MonzonDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.
Tina ChengDepartment of Oncology, Division of Medical Oncology, Tom Baker Cancer Centre, Calgary, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRisk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS). PATIENTS AND

methodsA total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines.

resultsHigh white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65.

conclusionsLiver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

Indexed as

Liver NeoplasmsMelanomaAlbuminsHumansImmune Checkpoint InhibitorsPrognosisRetrospective StudiesAlbuminsImmune Checkpoint Inhibitorsimmune checkpoint blockadeimmunotherapymelanomaprognostic modelreal world datarisk score

Identifiers

PMID37011230
PMCPMC10485285

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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.