Evidence map›Paper›PMID 40672056›Full record

ArticleThe Lancet regional health. Europe2025

Prediction of 90-day mortality among cancer patients with unplanned hospitalisation: a retrospective validation study of three prognostic scores.

Galip Can Uyar, Oriol Mirallas, Kadriye Başkurt, Berta Martin-Cullell, Enes Yeşilbaş, Jordi Recuero-Borau, Seher Kaya, Victor Navarro Garcés, Sevgi Eryıldız Yücel, Kreina Sharela Vega Cano and 7 more

Abstract read
In one paragraph

Article in The Lancet regional health. Europe, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

17 authors.

Galip Can UyarMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Oriol MirallasMedical Oncology Department, Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Kadriye BaşkurtMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Berta Martin-CullellMedical Oncology Department, Hospital de la Santa Creu I Sant Pau, Barcelona, 08041, Spain.
Enes YeşilbaşMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Jordi Recuero-BorauMedical Oncology Department, Hospital del Mar, Barcelona, 08003, Spain.
Seher KayaMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Victor Navarro GarcésOncology Data Science (ODysSey) Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Sevgi Eryıldız YücelMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Kreina Sharela Vega CanoMedical Oncology Department, Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Diego Gómez-PuertoMedical Oncology Department, Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Anna Pedrola GómezOncology Data Science (ODysSey) Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Clara Salva de TorresMedical Oncology Department, Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Ömür Berna Çakmak ÖksüzoğluMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.
Sonia SerradellMedical Oncology Department, Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Rodrigo DienstmannOncology Data Science (ODysSey) Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, 08035, Spain.
Osman SütcüoğluMedical Oncology Department, Etlik City Hospital, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate prediction of 90-day mortality in hospitalised cancer patients is critical for guiding personalised treatment decisions and optimising oncologic care. However, existing prognostic models often lack sufficient precision, particularly in distinguishing between high- and low-risk patients. In this retrospective study, we independently evaluated the prognostic performance of three scoring systems-the Prognostic Score for Hospitalised Cancer Patients (PROMISE), the Gustave Roussy Immune (GRIm) score, and the C-reactive protein-Triglyceride-Glucose Index (CTI)-in patients admitted for unplanned hospitalisations. Methods: This retrospective observational study was conducted at the Medical Oncology Clinic of Ankara Etlik City Hospital, Turkey, and included patients aged 18 years or older with a diagnosis of cancer who were hospitalised unexpectedly between February 2023 and February 2024. Laboratory data were retrieved from the institutional hospital information system. The PROMISE score was calculated using its original specification via the online tool (https://promise.vhio.net/). The GRIm score was calculated based on neutrophil-to-lymphocyte ratio (NLR), albumin, and lactate dehydrogenase (LDH). The CTI score was computed as: CTI = [0.412 × ln (C-reactive protein [CRP])] + ln [Triglyceride × Glucose/2], with a cut-off value of 4.78. A PROMISE-CTI Combined score was derived using regression-based weighting. Risk stratification was performed for all three scores using validated thresholds. Statistical analyses included Kaplan-Meier survival analysis, log-rank tests, univariable and multivariable logistic regression to assess predictors of 90-day mortality, and receiver operating characteristic (ROC) curve analysis to evaluate discriminatory performance. Findings: Among 1657 hospitalised cancer patients screened during the study period, 1109 met the inclusion criteria and were included in the analysis. PROMISE and GRIm scores were calculated for all 1109 patients, while CTI score was assessed in 333 patients with complete laboratory data. The 90-day mortality rate was 63.7% (n = 707). High PROMISE score (OR: 3.32, 95% CI: 1.40-7.86; p = 0.006) and high CTI score (OR: 2.85, 95% CI: 1.32-6.18; p = 0.008) were associated with increased 90-day mortality. Low PROMISE score (OR: 0.22, 95% CI: 0.10-0.49; p = 0.001) and low CTI score (OR: 0.35, 95% CI: 0.17-0.73; p = 0.003) were associated with reduced 90-day mortality. High GRIm score (OR: 1.83, 95% CI: 0.83-2.91; p = 0.07) and low GRIm score (OR: 0.73, 95% CI: 0.47-1.20; p = 0.08) were not significantly associated with 90-day mortality. The area under the curve (AUC) of the PROMISE-CTI Combined score was 0.884 (95% CI: 0.849-0.919; p < 0.0001). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the PROMISE-CTI Combined score were 92.4%, 81.1%, 85.3%, 89.6%, and 86.7%, respectively. Interpretation: The PROMISE score demonstrated strong discriminatory ability in predicting 90-day mortality among cancer patients admitted for unplanned hospitalisations. Integration of the CTI score further improved risk stratification by incorporating nutritional and inflammatory markers. The PROMISE-CTI Combined score may serve as a practical clinical tool for short-term prognostic assessment in this setting. Prospective, multicentre, randomised studies are needed to confirm the clinical utility and generalisability of the PROMISE-CTI Combined score. Funding: This study received no funding.

Indexed as

CancerMortalityNutritionPrognosisPROMISE score

Identifiers

PMID40672056
PMCPMC12266187

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