[Obstetrics and Gynecology - Femtech: how digital technologies are serving women's healthcare]. / Gynécologie ­ Obstétrique - FemTech : les nouvelles technologies au service de la santé de la femme.

Over the past ten years, a growing number of technological tools have been developed to improve women's health and well-being, grouped under the name FemTech. This growing field has the potential to improve gynecological care and covers solutions that are less invasive and more personalized to the patient's needs. Thanks to its world-renowned universities and hospitals, its high involvement in the research field and its strong biopharmaceutical sector, Romandy has demonstrated the rapid rise of start-ups dedicated to women's health, thus providing a promising landscape in the FemTech industry. Several Swiss FemTech companies yield innovative solutions related to fertility, menopause and gynecological instruments. This article aims to present the emerging Femtech companies in Romandy over the past years and their use among young women.

Au cours des 10 dernières années ont été développés un nombre croissant d'outils technologiques destinés à améliorer la santé et le bien-être des femmes, regroupés sous le nom de FemTech. Ce domaine qui ne cesse de croître a le potentiel d'améliorer la prise en charge gynécologique, de rendre les soins plus personnalisés et moins invasifs. Grâce à ses hôpitaux universitaires, ses instituts de recherche et son industrie pharmaceutique très développée, la Suisse romande compte des acteurs novateurs dans le secteur et a vu apparaître des start-up prometteuses. Plusieurs FemTech suisses proposent des solutions innovantes liées à la fertilité, à la ménopause ou aux instruments gynécologiques. Dans cet article, nous avons investigué les FemTech émergentes ces dernières années en Suisse romande et leur utilisation chez les jeunes femmes.

Acceptance, efficacy, and safety of COVID-19 vaccination in older patients with cancer.

PURPOSE: The COVID-19 vaccination campaign began in December 2020, in France, and primarily targeted the oldest people. Our study aimed to determine the level of acceptance of vaccination in a population of older patients with cancer. METHODS: From January 2021, we offered vaccination with the BNT162b2 COVID-19 vaccine to all patients 70 years and older referred to our geriatric oncology center in Marseille University Hospital (AP-HM) for geriatric assessment before initiation of an oncological treatment. Objectives were to evaluate acceptance rate of COVID-19 vaccination and to assess vaccine safety, reactogenicity, and efficacy two months after the first dose. RESULTS: Between January 18, 2021 and May 7, 2021, 150 older patients with cancer were offered vaccination after a geriatric assessment. The majority were men (61.3%), with a mean age of 81 years. The two most frequent primary tumors were digestive (29.4%) and thoracic (18%). The vaccine acceptance rate was 82.6% and the complete vaccination rate (2 doses) reached 75.3%. Among the vaccinated patients, 15.9% reported mild side effects after the first dose and 23.4% after the second dose, mostly arm pain and fatigue. COVID-19 cases were observed in 5.1% of vaccinated patients compared with 16.7% in unvaccinated patients. Of the 22 vaccinated patients who agreed to have their serum tested, 15 had antibodies against the spike protein at day 21 after the first dose. CONCLUSION: Our study showed a high acceptance rate of COVID-19 vaccination, with good tolerance in this frail population. These results highlight the benefits of organizing vaccination campaigns at the very beginning of oncological management in older patients. CLINICAL TRIAL REGISTRATION: This study was registered May 23, 2019 in ClinicalTrials.gov (NCT03960593).

Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs. METHODS: Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response. RESULTS: Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3% and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p < 0.0001; OR 1.8, p < 0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophil-to-lymphocyte ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03. CONCLUSION: Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

Efficacy of Immune Checkpoint Inhibitors in KRAS-Mutant Non-Small Cell Lung Cancer (NSCLC).

INTRODUCTION: KRAS mutation is the most frequent molecular alteration found in advanced NSCLC; it is associated with a poor prognosis without available targeted therapy. Treatment options for NSCLC have been recently enriched by the development of immune checkpoint inhibitors (ICIs), and data about its efficacy in patients with KRAS-mutant NSCLC are discordant. This study assessed the routine efficacy of ICIs in advanced KRAS-mutant NSCLC. METHODS: In this retrospective study, clinical data were extracted from the medical records of patients with advanced NSCLC treated with ICIs and with available molecular analysis between April 2013 and June 2017. Analysis of programmed death ligand 1 (PD-L1) expression was performed if exploitable tumor material was available. RESULTS: A total of 282 patients with ICI-treated (in the first line or more) advanced NSCLC (all histological subgroups) who were treated with ICIs (anti-programmed death 1, anti-PD-L1, or anti-cytotoxic T-lymphocyte associated protein 4 antibodies), including 162 (57.4%) with KRAS mutation, 27 (9.6%) with other mutations, and 93 (33%) with a wild-type phenotype, were identified. PD-L1 analysis was available for 128 patients (45.4%), of whom 45.3% and 19.5% had PD-L1 expression of 1% or more and 50%, respectively (49.5% and 21.2%, respectively, in the case of the 85 patients with KRAS-mutant NSCLC). No significant difference was seen in terms of objective response rates, progression-free survival, or overall survival between KRAS-mutant NSCLC and other NSCLC. No significant differences in overall survival or progression-free survival were observed between the major KRAS mutation subtypes (G12A, G12C, G12D, G12V, and G13C). In KRAS-mutant NSCLC, unlike in non-KRAS-mutant NSCLC, the efficacy of ICIs is consistently higher, even though not statistically significant, for patients with PD-L1 expression in 1% or more of tumor cells than for those with PD-L1 expression in less than 1% of tumor cells, and this finding is especially true when PD-L1 expression is high (PD-L1 expression ≥50%). CONCLUSION: For patients with KRAS-mutant NSCLC (all mutational subtypes), the efficacy of ICI is similar to that for patients with other types of NSCLC. PD-L1 expression seems to be more relevant for predicting the efficacy of ICIs in KRAS-mutant NSCLC than it is in other types of NSCLC.

Association Between Immune-related Adverse Events and Efficacy of Immune Checkpoint Inhibitors in Non-small-cell Lung Cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are available for first- and further lines of treatment of patients with advanced non-small-cell lung cancer (NSCLC). These treatments are associated with adverse events called immune-related adverse events (IRAEs). The incidence, diagnosis, and treatment of IRAEs are quite acknowledged; however, the link between IRAEs and the efficacy of ICIs requires further clarification. The objectives of this study were to assess the association between IRAEs incidence and severity and ICIs efficacy in patients with advanced NSCLC. METHODS: In this retrospective study, clinical, biological, treatment, and outcome data were collected from patients with advanced NSCLC who received at least 1 cycle of ICIs from April 2013 to February 2017. The primary endpoint was to assess the association of IRAEs incidence with overall survival (OS). Secondary endpoints were the association of IRAEs with progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). RESULTS: Overall, 270 patients were studied. The median OS was 14 months, median PFS was 2.6 months, ORR was 13%, and DCR was 51%. OS, PFS, and ORR were significantly better for patients with IRAEs compared with patients with no IRAEs, translating to median OS not reached versus 8.21 months, respectively (hazard ratio, 0.29; 95% confidence interval [CI], 0.18-0.46; P < .001); PFS was 5.2 versus 1.97 months (hazard ratio, 0.42; 95% CI, 0.32-0.57; P < .001); and ORR was 212.9% versus 5.7% (odds ratio, 4.9; 95% CI, 2.18-11.05; P < .001). CONCLUSIONS: This report presents the largest case series showing longer OS and PFS and better ORR when IRAEs occurred in a population of patients with advanced NSCLC treated with ICIs. The biological background for this phenomenon is being explored prospectively.