RESUMEN
Background: Treatment options for patients with urothelial cancer (UC) refractory to platinum and immunotherapy are limited and survival is short. Enfortumab vedotin (EV) is a monoclonal anti-NECTIN4 antibody conjugated to monomethyl auristatin. It was recently approved because of superior survival in comparison to standard-of-care (SOC) chemotherapy. Real-world patients, however, often have worse characteristics than patients included in clinical trials. Objective: To analyze the efficacy and safety of EV in a cohort of real-world patients. Design setting and participants: Retrospective data were collected from 23 hospitals and private practices for patients with metastatic and previously treated UC who received EV either when reimbursed by their insurance company before European Medicines Agency (EMA) approval, within a compassionate use program, or as SOC treatment after EMA approval. Imaging and therapy management were in accordance with local standards. Outcome measurements and statistical analysis: Adverse events (AEs) were reported according to Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 criteria. Objective responses were evaluated according to Response Evaluation Criteria in Solid Tumors version 1.1. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Results and limitations: The median age for the 125 eligible patients was 66 yr (range 31-89). The Eastern Cooperative Oncology Group performance status (ECOG PS) was 0-1 for 76.0%, 2-4 for 13.6%, and unknown for 10.4% of patients. EV was administered in the fourth or later line for 44.8% of patients. The overall response rate was 41.6% (partial response 39.2%, complete response 2.4%). Median OS was 10.0 months (mo) (95% confidence interval 7.20-12.80) and median PFS was 5.0 mo (95% confidence interval 4.34-5.67). For patients with ECOG PS of 0-1, median OS was 14 mo. Any-grade AEs were observed in 67.2% and CTCAE grade ≥3 AEs in 30.4%. The most common AEs were peripheral sensory neuropathy and skin toxicity. Three fatal events (pneumonia, pneumonitis) occurred. Limitations include the retrospective design and short follow-up. Conclusions: Administration of EV for real-world patients was feasible with an acceptable toxicity profile. No new safety signals were reported. Antitumor activity in our cohort was comparable to data previously reported for trials. In summary, our results support the use of EV in patients with metastatic UC. Patient summary: Enfortumab vedotin is a medication that improved the survival of patients with bladder cancer in comparison to standard chemotherapy in clinical trials. However, patients included in clinical trials are highly selected and results for toxicities and improvements in survival do not always transfer to the real-world setting. We analyzed data for 125 patients who were treated with enfortumab vedotin. Our results are comparable to the outcomes from clinical trials regarding the safety and efficacy of this treatment.
RESUMEN
BACKGROUND: Increasing life expectancy results in more elderly people struggling with age related diseases and functional conditions. This poses huge challenges towards establishing new approaches for maintaining health at a higher age. An important aspect for age related deterioration of the general patient condition is frailty. The frailty syndrome is associated with a high risk for falls, hospitalization, disability, and finally increased mortality. Using predictive data mining enables the discovery of potential risk factors and can be used as clinical decision support system, which provides the medical doctor with information on the probable clinical patient outcome. This enables the professional to react promptly and to avert likely adverse events in advance. METHODS: Medical data of 474 study participants containing 284 health related parameters, including questionnaire answers, blood parameters and vital parameters from the Toledo Study for Healthy Aging (TSHA) was used. Binary classification models were built in order to distinguish between frail and non-frail study subjects. RESULTS: Using the available TSHA data and the discovered potential predictors, it was possible to design, develop and evaluate a variety of different predictive models for the frailty syndrome. The best performing model was the support vector machine (SVM, 78.31%). Moreover, a methodology was developed, making it possible to explore and to use incomplete medical data and further identify potential predictors and enable interpretability. CONCLUSIONS: This work demonstrates that it is feasible to use incomplete, imbalanced medical data for the development of a predictive model for the frailty syndrome. Moreover, potential predictive factors have been discovered, which were clinically approved by the clinicians. Future work will improve prediction accuracy, especially with regard to separating the group of frail patients into frail and pre-frail ones and analyze the differences among them.
