一种针对接受积极全身治疗时需要住院的晚期癌症患者的新型死亡率预测模型。

A New Mortality Prediction Model in Advanced Stage Cancer Patients Requiring Hospitalisation while Receiving Active Systemic Therapy.

作者信息

Karaboyun Kubilay, Iriagac Yakup, Cavdar Eyyup, Avci Okan, Seber Erdogan Selcuk

机构信息

Department of Medical Oncology, Faculty of Medicine, Tekirdag Namik Kemal University, Tekirdag, Turkiye.

出版信息

J Coll Physicians Surg Pak. 2023 May;33(5):548-553. doi: 10.29271/jcpsp.2023.05.548.

DOI:10.29271/jcpsp.2023.05.548

PMID:37190691

Abstract

OBJECTIVE

To predict short and long-term mortality in patients who were admitted to the emergency department and then hospitalised unplanned in medical oncology-ward.

STUDY DESIGN

An observational study. Place and Duration of the Study: Department of Medical Oncology, Tekirdag Namik Kemal University Hospital, Tekirdag, Turkiye, from May 2021 to May 2022.

METHODOLOGY

Consecutive patients admitted to the emergency department with unplanned hospitalisation in the oncology ward, were included. Patients receiving treatment with the curative intent, patients hospitalised for febrile neutropenia, and terminally ill patients requiring intensive care unit follow-up at admission were excluded from the study. Univariate and multivariate logistic regression analyses were used to identify predictive factors for short and long-term mortality-dependent variables.

RESULTS

This study included 253 advanced cancer patients. The number of patients who died in the ward within 10 days (short-term mortality) was 28 (11.1%). Ninety patients (35.6%) died afterwards anytime in the ward during the study (long-term mortality). In the multivariate analysis established for short-term mortality, higher ALT (OR = 6.75, 95% CI: 2.09 - 21.85, p=0.001), rapid deterioration in performance status (OR = 5.49, 95% CI: 1.81-16.67, p=0.003), higher CRP (OR = 5.86, 95% CI: 1.20-28.53, p=0.029), higher procalcitonin (OR = 7.94, 95% CI: 0.99 - 63.82, p=0.051), and higher lactate (OR = 2.47, 95% CI: 0.94-6.51, p=0.067) showed significant predictive features.

CONCLUSION

The decision of whether to continue treatment or not is challenging in cancer patients who require unplanned hospitalisation while receiving palliative systemic therapy. New mortality estimation models can be used in making the transition from life-long to palliative treatments.

KEY WORD

Mortality prediction, Hospitalisation, Estimation of survival, Chemotherapy.

摘要

目的

预测急诊入院后在医学肿瘤病房非计划住院患者的短期和长期死亡率。

研究设计

一项观察性研究。研究地点和时间：2021年5月至2022年5月，土耳其泰基尔达纳米克·凯末尔大学医院医学肿瘤学系。

方法

纳入连续在急诊科就诊后在肿瘤病房非计划住院的患者。接受根治性治疗的患者、因发热性中性粒细胞减少症住院的患者以及入院时需要重症监护病房随访的晚期患者被排除在研究之外。采用单因素和多因素逻辑回归分析来确定短期和长期死亡率相关变量的预测因素。

结果

本研究纳入了253例晚期癌症患者。10天内在病房死亡的患者数量（短期死亡率）为28例（11.1%）。90例患者（35.6%）在研究期间的任何时间在病房死亡（长期死亡率）。在针对短期死亡率建立的多因素分析中，较高的谷丙转氨酶（OR = 6.75，95%CI：2.09 - 21.85，p = 0.001）、体能状态快速恶化（OR = 5.49，95%CI：1.81 - 16.67，p = 0.003）、较高的C反应蛋白（OR = 5.86，95%CI：1.20 - 28.53，p = 0.029）、较高的降钙素原（OR = 7.94，95%CI：0.99 - 63.82，p = 0.051）和较高的乳酸（OR = 2.47，95%CI：0.94 - 6.51，p = 0.067）显示出显著的预测特征。