Satheeshkumar Poolakkad S, Sonis Stephen T, Epstein Joel B, Pili Roberto
Department of Medicine, Division of Hematology and Oncology, University at Buffalo, Buffalo, NY 14203, USA.
Divisions of Oral Medicine, Brigham and Women's Hospital and the Dana-Faber Cancer Institute, Boston, MA 02115, USA.
Cancers (Basel). 2025 Mar 27;17(7):1121. doi: 10.3390/cancers17071121.
BACKGROUND/OBJECTIVES: Social determinants of health (SDOHs) are especially impactful with respect to emergency reliance among patients with cancer.
To better predict the extent to which SDOHs affect emergency admissions in homeless patients with metastatic disease, we employed machine learning models, Lasso, ridge, random forest (RF), and elastic net (EN) regression. We also examined prostate cancer (PC), breast cancer (BC), lung (LC) cancer, and cancers of the lip, oral cavity, and pharynx (CLOP) for association between key SDOH variables-homelessness and living alone-and clinical outcomes. For this, we utilized generalized linear models to assess the association while controlling for patient and clinical characteristics. We used the United States National Inpatient Sample database for this study.
There were 2635 (weighted) metastatic cancer patients with homelessness. Transfer from another facility or not, elective admission or not, deficiency anemia, alcohol dependence, weekend admission or not, and blood loss anemia were the important predictors of emergency admission. C-statistics were associated with Lasso (train AUC-0.85; test AUC-0.86), ridge (85, 88), RF (0.96, 0.85), and EN (0.83, 0.80), respectively. In the adjusted analysis, PC homelessness was significantly associated with anxiety and depression (5.15, 95% CI: 3.17-8.35) and a longer LOS (1.96; 95% CI: 1.03-3.74). Findings were comparable in the BC, LC, and CLOP cohorts. Cancer patients with poor SDOHs presented with the worst clinical outcomes.
Cancer patients with poor SDOH presented with worst clinical outcomes. The findings of this study highlight a vacuum in the cancer literature, and the recommendations stress the value of social support in achieving a better prognosis and Quality of life.
背景/目的：健康的社会决定因素（SDOHs）对癌症患者的急诊依赖影响尤为显著。
为了更好地预测SDOHs对转移性疾病无家可归患者急诊入院的影响程度，我们采用了机器学习模型、套索回归、岭回归、随机森林（RF）回归和弹性网（EN）回归。我们还研究了前列腺癌（PC）、乳腺癌（BC）、肺癌（LC）以及唇、口腔和咽癌（CLOP），以探讨关键SDOH变量——无家可归和独居——与临床结局之间的关联。为此，我们使用广义线性模型在控制患者和临床特征的同时评估这种关联。本研究使用了美国国家住院样本数据库。
有2635名（加权）转移性癌症无家可归患者。是否从其他机构转来、是否择期入院、是否存在缺铁性贫血、酒精依赖、是否周末入院以及失血性贫血是急诊入院的重要预测因素。C统计量分别与套索回归（训练集AUC为0.85；测试集AUC为0.86）、岭回归（0.85，0.88）、随机森林回归（0.96，0.85）和弹性网回归（0.83，0.80）相关。在调整分析中，PC患者无家可归与焦虑和抑郁显著相关（5.15，95%置信区间：3.17 - 8.35），住院时间更长（1.96；95%置信区间：1.03 - 3.74）。在BC、LC和CLOP队列中也有类似发现。SDOHs较差的癌症患者临床结局最差。
SDOHs较差的癌症患者临床结局最差。本研究结果凸显了癌症文献中的空白，建议强调社会支持对实现更好预后和生活质量的价值。
