Health Services and Outcomes Research, National Healthcare Group, Annex @ National Skin Centre, 1 Mandalay Road, Singapore, 308205, Singapore.
Department of Palliative Medicine, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore.
BMC Pulm Med. 2024 Aug 30;24(1):429. doi: 10.1186/s12890-024-03233-0.
Patients with chronic lung diseases (CLDs), defined as progressive and life-limiting respiratory conditions, experience a heavy symptom burden as the conditions become more advanced, but palliative referral rates are low and late. Prognostic tools can help clinicians identify CLD patients at high risk of deterioration for needs assessments and referral to palliative care. As current prognostic tools may not generalize well across all CLD conditions, we aim to develop and validate a general model to predict one-year mortality in patients presenting with any CLD.
A retrospective cohort study of patients with a CLD diagnosis at a public hospital from July 2016 to October 2017 was conducted. The outcome of interest was all-cause mortality within one-year of diagnosis. Potential prognostic factors were identified from reviews of prognostic studies in CLD, and data was extracted from electronic medical records. Missing data was imputed using multiple imputation by chained equations. Logistic regression models were developed using variable selection methods and validated in patients seen from January 2018 to December 2019. Discriminative ability, calibration and clinical usefulness of the model was assessed. Model coefficients and performance were pooled across all imputed datasets and reported.
Of the 1000 patients, 122 (12.2%) died within one year. Patients had chronic obstructive pulmonary disease or emphysema (55%), bronchiectasis (38%), interstitial lung diseases (12%), or multiple diagnoses (6%). The model selected through forward stepwise variable selection had the highest AUC (0.77 (0.72-0.82)) and consisted of ten prognostic factors. The model AUC for the validation cohort was 0.75 (0.70, 0.81), and the calibration intercept and slope were - 0.14 (-0.54, 0.26) and 0.74 (0.53, 0.95) respectively. Classifying patients with a predicted risk of death exceeding 0.30 as high risk, the model would correctly identify 3 out 10 decedents and 9 of 10 survivors.
We developed and validated a prognostic model for one-year mortality in patients with CLD using routinely available administrative data. The model will support clinicians in identifying patients across various CLD etiologies who are at risk of deterioration for a basic palliative care assessment to identify unmet needs and trigger an early referral to palliative medicine.
Not applicable (retrospective study).
慢性肺部疾病（CLD）患者的病情呈进行性发展且危及生命，随着病情的发展，他们的症状负担很重，但姑息治疗的转诊率很低且很滞后。预后工具可以帮助临床医生识别出病情恶化风险较高的 CLD 患者，以便进行需求评估并转至姑息治疗。由于当前的预后工具可能无法很好地适用于所有 CLD 疾病，因此我们旨在开发和验证一种可预测任何 CLD 患者一年内死亡率的通用模型。
对 2016 年 7 月至 2017 年 10 月在一家公立医院就诊的 CLD 患者进行回顾性队列研究。感兴趣的结局是诊断后一年内的全因死亡率。从 CLD 的预后研究综述中确定了潜在的预后因素，并从电子病历中提取了数据。使用链状方程的多重插补法对缺失数据进行了插补。使用变量选择方法开发了逻辑回归模型，并在 2018 年 1 月至 2019 年 12 月就诊的患者中进行了验证。评估了模型的判别能力、校准和临床实用性。在所有插补数据集中汇总了模型系数和性能，并进行了报告。
在 1000 名患者中，有 122 名（12.2%）在一年内死亡。患者患有慢性阻塞性肺疾病或肺气肿（55%）、支气管扩张症（38%）、间质性肺疾病（12%）或多种诊断（6%）。通过逐步向前变量选择选择的模型具有最高的 AUC（0.77（0.72-0.82）），并包含十个预后因素。验证队列的模型 AUC 为 0.75（0.70，0.81），校准截距和斜率分别为-0.14（-0.54，0.26）和 0.74（0.53，0.95）。将预测死亡风险超过 0.30 的患者分类为高危患者，该模型将正确识别出 10 名死者中的 3 名和 10 名幸存者中的 9 名。
我们使用常规可用的行政数据为 CLD 患者开发并验证了一种用于预测一年内死亡率的预后模型。该模型将有助于临床医生识别出各种 CLD 病因的患者，这些患者的病情恶化风险较高，需要进行基本的姑息治疗评估，以确定未满足的需求并尽早转至姑息医学。
不适用（回顾性研究）。
