Development of a prognostic model to predict 90-day mortality in hospitalised cancer patients (PROMISE tool): a prospective observational study

IF 13.6 Q1 HEALTH CARE SCIENCES & SERVICES

Lancet Regional Health-Europe Pub Date : 2024-11-01 DOI:10.1016/j.lanepe.2024.101063

Oriol Mirallas , Berta Martin-Cullell , Víctor Navarro , Kreina Sharela Vega , Jordi Recuero-Borau , Diego Gómez-Puerto , Daniel López-Valbuena , Clara Salva de Torres , Laura Andurell , Anna Pedrola , Roger Berché , Fiorella Palmas , José María Ucha , Guillermo Villacampa , Alejandra Rezqallah , Judit Sanz-Beltran , Rafael Bach , Sergio Bueno , Cristina Viaplana , Gaspar Molina , Joan Carles

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引用次数: 0

Abstract

Background

Prognostic factors for ambulatory oncology patients have been described, including Eastern Cooperative Oncology Group (ECOG), tumor stage and malnutrition. However, there is no firm evidence on which variables best predict mortality in hospitalized patients receiving active systemic treatment. Our main goal was to develop a predictive model for 90-day mortality upon admission.

Methods

Between 2020 and 2022, we prospectively collected data from three sites for cancer patients with hospitalizations. Those with metastatic disease receiving systemic therapy in the 6 months before unplanned admission were eligible to this study. The least absolute shrinkage and selection operator (LASSO) method was used to select the most relevant factors to predict 90-day mortality at admission. A multivariable logistic regression was fitted to create the PROgnostic Score for Hospitalized Cancer Patients (PROMISE) score. The score was developed in a single-center training cohort and externally validated.

Findings

Of 1658 hospitalized patients, 1009 met eligibility criteria. Baseline demographics, patient and disease characteristics were similar across cohorts. Lung cancer was the most common tumor type in both cohorts. Factors associated with higher 90-day mortality included worse ECOG, stable/progressive disease, low levels of albumin, increased absolute neutrophil count, and high lactate dehydrogenase. The c-index after bootstrap correction was 0.79 (95% CI, 0.75–0.82) and 0.74 (95% CI, 0.68–0.80) in the training and validation cohorts, respectively. A web tool (https://promise.vhio.net/) was developed to facilitate the clinical deployment of the model.

Interpretation

The PROMISE tool demonstrated high performance for identifying metastatic cancer patients who are alive 90 days after an unplanned hospitalization. This will facilitate healthcare providers with rational clinical decisions and care planning after discharge.

Funding

Merck S.L.U., Spain.

查看原文本刊更多论文

开发预测住院癌症患者 90 天死亡率的预后模型（PROMISE 工具）：前瞻性观察研究

背景已经描述了非住院肿瘤患者的诊断因素，包括东部合作肿瘤学组（ECOG）、肿瘤分期和营养不良。然而，目前还没有确凿证据表明哪些变量最能预测接受积极系统治疗的住院患者的死亡率。我们的主要目标是建立一个入院后 90 天死亡率的预测模型。方法在 2020 年至 2022 年期间，我们从三个地点前瞻性地收集了住院癌症患者的数据。计划外入院前 6 个月内接受过系统治疗的转移性疾病患者有资格参与本研究。我们采用最小绝对收缩和选择算子（LASSO）方法来选择预测入院时 90 天死亡率的最相关因素。通过多变量逻辑回归，得出了住院癌症患者预后评分（PROMISE）。在 1658 名住院患者中，有 1009 人符合资格标准。不同队列的基线人口统计学特征、患者特征和疾病特征相似。肺癌是两个队列中最常见的肿瘤类型。与 90 天死亡率较高相关的因素包括 ECOG 较差、病情稳定/进展、白蛋白水平较低、绝对中性粒细胞计数增加以及乳酸脱氢酶较高。经过引导校正后，训练队列和验证队列的 c 指数分别为 0.79（95% CI，0.75-0.82）和 0.74（95% CI，0.68-0.80）。为方便临床应用该模型，我们还开发了一个网络工具（https://promise.vhio.net/）。释义PROMISE工具在识别意外住院90天后仍存活的转移性癌症患者方面表现出色。这将有助于医疗服务提供者在患者出院后做出合理的临床决策和护理计划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Lancet Regional Health-Europe Multiple-

CiteScore

19.90

自引率

1.40%

发文量

260

审稿时长

9 weeks

期刊介绍： The Lancet Regional Health – Europe, a gold open access journal, is part of The Lancet's global effort to promote healthcare quality and accessibility worldwide. It focuses on advancing clinical practice and health policy in the European region to enhance health outcomes. The journal publishes high-quality original research advocating changes in clinical practice and health policy. It also includes reviews, commentaries, and opinion pieces on regional health topics, such as infection and disease prevention, healthy aging, and reducing health disparities.