The impact of comorbidities, neutrophil-to-lymphocyte ratio, and drug toxicities on quality of life in lung cancer patients receiving EGFR-TKI therapy.

BACKGROUND: Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are used as the standard first-line treatment for patients with advanced EGFR-mutated non-small cell lung cancer (NSCLC). However, the impact of comorbidities and treatment toxicities on quality of life (QoL) was seldom investigated. OBJECTIVE: We aimed to investigate the association of comorbidities, adverse events (AEs), and QoL in treatment-naïve advanced NSCLC patients receiving EGFR-TKI treatments. METHODS: This multi-center prospective observational study was conducted to evaluate QoL and AEs at baseline, the 2nd, 4th, 12th, and 24th week. Clinical characteristics, comorbidities, and pre-treatment laboratory data were recorded. QoL was assessed by using the summary score of the EORTC QLQ-C30 and the dermatology life quality index. The impact of comorbidities, neutrophil-to-lymphocyte ratio (NLR), and AEs on QoL was analyzed by generalized estimating equations. RESULTS: A total of 121 patients were enrolled. Diarrhea (p = 0.033), anorexia (p < 0.001), and NLR ≥4 (p = 0.017) were significantly associated with a QoL impairment. Among skin toxicities, acneiform rash (p = 0.002), pruritus (p = 0.002), visual analogue scale for pruritus (≥3 and < 7, p = 0.006; ≥7, p = 0.001) and pain (1-3, p = 0.041) were associated with a QoL impairment. No significant association was found between comorbidities and QoL changes. CONCLUSION: Diarrhea, anorexia, skin pain, and pruritus may cause a deterioration in QoL in patients receiving EGFR-TKI therapy. NLR may be a potential predictive factor for QoL impairment. Aggressive management and close monitoring for these clinical factors are crucial to improve QoL.

Cost Utility Analysis of Multidisciplinary Postacute Care for Stroke: A Prospective Six-Hospital Cohort Study.

Background: Few studies have compared the optimal duration and intensity of organized multidisciplinary neurological/rehabilitative care delivered in a regional/district hospital with the standard rehabilitative care delivered in the general neurology/rehabilitation ward of a medical center. This study measured functional outcomes and conducted cost-utility analysis of an organized multidisciplinary postacute care (PAC) project in secondary care compared with standard rehabilitative care delivered in tertiary care. Methods: This prospective cohort study enrolled 1,476 patients who had a stroke between March 2014 and March 2018 and had a modified Rankin scale score of 2-4. After exact matching for age ± 1 year, sex, year of stroke diagnosis, nasogastric tube, and Foley catheter and propensity score matching for the other covariates, we obtained 120 patients receiving PAC (the PAC group) from four regional/district hospitals and 120 patients not receiving PAC (the non-PAC group) from two medical centers. Results: At baseline, the non-PAC group showed significantly better functional outcomes than the PAC group, including EuroQol-5 dimensions (EQ-5D), Mini-Mental State Examination (MMSE) and Barthel index (BI). During weeks 7-12 of rehabilitation, improvements in all functional outcomes were significantly larger in the PAC group (P < 0.001) except for Functional Oral Intake Scale (FOIS). Cost-utility analysis revealed that the PAC group had a significantly lower mean (± standard deviation) of direct medical costs (US$3,480 ± $1,758 vs. US$3,785 ± $3,840, P < 0.001) and a significantly higher average gain of quality-adjusted life years (0.1993 vs. 0.1233, P < 0.001). The PAC project was an economically "dominant" strategy. Conclusions: The PAC project saved costs and significantly improved the functional outcomes of patients with stroke with slight to moderately severe disabilities. Randomized control trials are required to corroborate these results.

Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study.

Background: Machine learning algorithms for predicting 30-day stroke readmission are rarely discussed. The aims of this study were to identify significant predictors of 30-day readmission after stroke and to compare prediction accuracy and area under the receiver operating characteristic (AUROC) curve in five models: artificial neural network (ANN), K nearest neighbor (KNN), random forest (RF), support vector machine (SVM), naive Bayes classifier (NBC), and Cox regression (COX) models. Methods: The subjects of this prospective cohort study were 1,476 patients with a history of admission for stroke to one of six hospitals between March, 2014, and September, 2019. A training dataset (n = 1,033) was used for model development, and a testing dataset (n = 443) was used for internal validation. Another 167 patients with stroke recruited from October, to December, 2019, were enrolled in the dataset for external validation. A feature importance analysis was also performed to identify the significance of the selected input variables. Results: For predicting 30-day readmission after stroke, the ANN model had significantly (P < 0.001) higher performance indices compared to the other models. According to the ANN model results, the best predictor of 30-day readmission was PAC followed by nasogastric tube insertion and stroke type (P < 0.05). Using a machine learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. Conclusion: Using a machine-learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. For stroke patients who are candidates for PAC rehabilitation, these predictors have practical applications in educating patients in the expected course of recovery and health outcomes.

Multidiscipline Stroke Post-Acute Care Transfer System: Propensity-Score-Based Comparison of Functional Status.

Few studies have investigated the characteristics of stroke inpatients after post-acute care (PAC) rehabilitation, and few studies have applied propensity score matching (PSM) in a natural experimental design to examine the longitudinal impacts of a medical referral system on functional status. This study coupled a natural experimental design with PSM to assess the impact of a medical referral system in stroke patients and to examine the longitudinal effects of the system on functional status. The intervention was a hospital-based, function oriented, 12-week to 1-year rehabilitative PAC intervention for patients with cerebrovascular diseases. The average duration of PAC in the intra-hospital transfer group (31.52 days) was significantly shorter than that in the inter-hospital transfer group (37.1 days) (p < 0.001). The intra-hospital transfer group also had better functional outcomes. The training effect was larger in patients with moderate disability (Modified Rankin Scale, MRS = 3) and moderately severe disability (MRS = 4) compared to patients with slight disability (MRS = 2). Intensive post-stroke rehabilitative care delivered by per-diem payment is effective in terms of improving functional status. To construct a vertically integrated medical system, strengthening the qualified local hospitals with PAC wards, accelerating the inter-hospital transfer, and offering sufficient intensive rehabilitative PAC days are the most essential requirements.