No outside funding supported this study. The authors declare that they have no affiliations with or financial interests in any company, product, or service described in the manuscript. Study concept and design were contributed by Sierra-Sánchez, Martínez-Bautista, Baena-Cañada, and González-Carrascosa Vega. Martínez-Bautista, García-Martín, Suárez-Carrascosa, and González-Carrascosa Vega collected the data, which was interpreted by Sierra-Sánchez, Martínez-Bautista, Baena-Cañada, and González-Carrascosa Vega. The manuscript was written by Sierra-Sánchez and González-Carrascosa Vega and revised by Sierra-Sánchez, Martínez-Bautista, Baena-Cañada, and González-Carrascosa Vega.

Breast cancer is one of the most frequent malignancies. The aim of the article is to analyse the cost-utility ratio and budgetary impact of talazoparib treatment for patients with locally advanced or metastatic gBRCA þ breast cancer from the perspective of the Spanish National Health System. Analyses were based on the EMBRACA clinical trial and the model was constructed according to "partitioned survival analysis". Two scenarios were considered in order to compare talazoparib with the alternatives of capecitabine, vinorelbine and eribulin: 1. Chemotherapy in patients pre-treated with anthracyclines/taxanes and, 2. A second-and subsequent-line treatment option. Treatment types following relapse were recorded in the mentioned clinical trial. The effectiveness measure used was quality-adjusted life years (QALY). The average health cost of patients treated at 43 months with talazoparib was 84,360.86V, whilst current treatment costs were 26,683.90V. The effectiveness of talazoparib was 1.93 years of survival (1.09 QALY) relative to 1.58 years (0.83 QALY) in the treatment group. The incremental cost-utility ratio was 252,420.04V/QALY. This represents the additional cost required to earn an additional QALY when changing from regular treatment to talazoparib. Regarding budgetary impact, the number of patients susceptible to receiving treatment with between 94 and 202 talazoparib was estimated, according to scenario and likelihood. The 3-year cost difference was between 6.9 and 9 million euros. The economic evaluation conducted shows an elevated incremental cost-utility ratio and budgetary impact. Taking these results into account, the price of talazoparib would have to be lower than that taken as a reference to reach the cost-utility thresholds.

Cystinosis is a rare genetic disorder characterized by the accumulation of cystine crystals in different tissues and organs. Although renal damage prevails during initial stages, the deposition of cystine crystals in the cornea causes severe ocular manifestations. At present, cysteamine is the only topical effective treatment for ocular cystinosis. The lack of investment by the pharmaceutical industry, together with the limited stability of cysteamine, make it available only as two marketed presentations (Cystaran® and Cystadrops®) and as compounding formulations prepared in pharmacy departments. Even so, new drug delivery systems (DDSs) need to be developed, allowing more comfortable dosage schedules that favor patient adherence. In the last decades, different research groups have focused on the development of hydrogels, nanowafers and contact lenses, allowing a sustained cysteamine release. In parallel, different determination methods and strategies to increase the stability of the formulations have also been developed. This comprehensive review aims to compile all the challenges and advances related to new cysteamine DDSs, analytical determination methods, and possible future therapeutic alternatives for treating cystinosis.

BI present a high ARC during their MP after their commercialization, without any efficacy or safety difficulties. Knowledge of this might increase confidence for biosimilars.

The clinical course of COVID-19 is highly variable. It is therefore essential to predict as early and accurately as possible the severity level of the disease in a COVID-19 patient who is admitted to the hospital. This means identifying the contributing factors of mortality and developing an easy-to-use score that could enable a fast assessment of the mortality risk using only information recorded at the hospitalization. A large database of adult patients with a confirmed diagnosis of COVID-19 (n = 15,628; with 2,846 deceased) admitted to Spanish hospitals between December 2019 and July 2020 was analyzed. By means of multiple machine learning algorithms, we developed models that could accurately predict their mortality. We used the information about classifiers’ performance metrics and about importance and coherence among the predictors to define a mortality score that can be easily calculated using a minimal number of mortality predictors and yielded accurate estimates of the patient severity status. The optimal predictive model encompassed five predictors (age, oxygen saturation, platelets, lactate dehydrogenase, and creatinine) and yielded a satisfactory classification of survived and deceased patients (area under the curve: 0.8454 with validation set). These five predictors were additionally used to define a mortality score for COVID-19 patients at their hospitalization. This score is not only easy to calculate but also to interpret since it ranges from zero to eight, along with a linear increase in the mortality risk from 0% to 80%. A simple risk score based on five commonly available clinical variables of adult COVID-19 patients admitted to hospital is able to accurately discriminate their mortality probability, and its interpretation is straightforward and useful.