First-line avelumab for patients with PD-L1-positive metastatic or locally advanced urothelial cancer who are unfit for cisplatin

BACKGROUND

Cisplatin-based chemotherapy is the most recommended treatment for metastatic urothelial cancer (mUC). However, about 50% of patients are considered to be cisplatin ineligible. Anti-PD1/PD-L1 therapies have, nevertheless, increased the options available to clinicians and are especially valuable for treating these patients. This study therefore tested the activity and safety of avelumab as first-line therapy for mUC.

PATIENTS AND METHODS

Patients with mUC who were ineligible for cisplatin-based chemotherapy were screened centrally for PD-L1 expression and only those with a tumour proportion score (TPS) ≥5% were enrolled in the trial. The primary endpoint was 1-year overall survival (OS), and the secondary endpoints were median OS, median PFS, the ORR, the duration of the response, safety, and tolerability. All the survival rates were estimated with the Kaplan-Meier product-limit methodology and compared across groups using the log-rank test.

RESULTS

198 patients were screened, with 71 (35.9%) whose PD-L1 expression was ≥5% enrolled in the study. The median age was 75 years, bladder cancer was the primary tumour in 73.2% of cases, and 25.3% had liver metastases. The main reasons for the cisplatin ineligibility were a low rate of creatinine clearance (< 60 ml/min), present in 70.4% of patients, and an ECOG performance status of 2, which affected 31%. The median OS was 10.0 months (95% CI, 5.5-14.5) and 43% of patients were alive at one year. A complete response was achieved in 8.5% of cases and 15.5% had a partial response. Adverse any-grade and high-grade events occurred in 49.3% and 8.5% of patients, respectively. A grade 3 infusion reaction was the only high-grade treatment-related adverse event. No treatment-related deaths were reported.

CONCLUSIONS

This ARIES trial confirmed the activity and safety of avelumab for treating mUC, adding a new therapy option to the armamentarium of checkpoint inhibitors already approved for platinum-ineligible, locally advanced/mUC.

An accelerated procedure for recursive feature ranking on microarray data

We describe a new wrapper algorithm for fast feature ranking in classification problems. The Entropy-based Recursive Feature Elimination (E-RFE) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data.

Ixodes ricinus (Acari: Ixodidae) infestation on roe deer (Capreolus capreolus) in Trentino, Italian Alps

The most important tick-deer system potentially supporting the epidemiology of Lyme disease in the Italian Alps is that regarding Ixodes ricinus (L.) and roe deer (Capreolus capreolus L.). In this study, the pattern of tick infestation on 562 male roe deer harvested in September 1994 in 56 game districts of Trentino, Northern Italy, was assessed. The prevalence and density of infestation by I. ricinus were analyzed by a model based on classification and regression trees (CART), using both discrete and continuous variables concerning environmental and host parameters. The model discriminated attitude and host density as the 2 variables having the greatest effect on the prevalence and density of infestation of deer; the levels of infestation were higher at an altitude below 1125 m or at roe deer densities over 8.5 head per 100 ha. The density of tick infestation tended to be higher in older roe deer.

Classification tree methods for analysis of mesoscale distribution of Ixodes ricinus (Acari:Ixodidae) in Trentino, Italian Alps

Cases of Lyme disease and tick-borne encephalitis were recognized recently in the Province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on classification and regression trees (CART), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from extensive sampling carried out by standard methods in 99 sites over an area of approximately 2,700 km2 in the Province of Trento. A series of environmental parameters were recorded from each site and population densities of roe deer, Capreolus capreolus (L.), were considered. The CART model discriminates 2 variables that appear to have the greatest effect on the mesoscale occurrence of ticks: altitude and geological substratum, with a drastic decrease of tick frequency above an altitude of approximately 1,100 m and on volcanic substrata. The model is effective in identifying the mesoscale areas at greater potential risk, with a relatively low sampling effort.