Real-time genotyping-based breast cancer risk assessment in MyPeBS, an international randomized trial in the general population comparing risk-stratified to standard breast cancer screening (BCS)

Background: Risk-stratified BCS, integrating personal, familial variables and a polygenic risk score (PRS) is a promising strategy that may improve current BCS outcomes. Real-time risk assessment and field implementation are some of the main challenges for such an approach. Methods: MyPeBS is an ongoing EU-funded international randomized trial running in 6 countries. Eligible women (wn) aged 40-70 are randomized 1:1 between continuing standard organized BCS as recommended in their participating country/region and switching to risk-stratified BCS, in which BCS schedule and modalities are adapted to the individual predicted 5-year risk of invasive BC (IBC). Primary endpoint is 4-year incidence of stage 2 and higher BC. Secondary endpoints include PROs. 5-year IBC risk is estimated using the Mammorisk® BCSC-derived or the Tyrer Cuzick risk score and the centrally-determined PRS313 obtained from a saliva sample and calibrated for national BC incidence and age. We aim to describe 1) the feasibility of real-time assessment of BC risk and 2) the characteristics and risk profiles of the participants. Results: As of Sept. 7, 2021, 16,550 wn had been randomized. 29% were aged <50 (median age 54 (range 40-70), 13% had a previous benign breast biopsy, 40% a mammographic breast density C or D, 19% a 1st degree family history of breast or ovarian cancer;72% had tertiary education. 36% were estimated at low risk (<1% risk of IBC at 5 years), 29% at average risk, and 35% at high (34%) or very high risk (1%) (>1.67% and >6% risk, respectively). Only 2.5% of DNA extractions were not usable for genotyping, due to DNA concentration or quality;and 98.8% of the eligible DNA samples were successfully genotyped. Median turnover time from saliva sampling to risk result available was 11 weeks despite the COVID pandemic (currently 7 weeks). Conclusions: Real-time BC risk assessment based on a large set of polymorphisms, family, screening and hormonal history, and breast density is feasible within organized screening programmes. Participants are so far representative of different categories with some over-representation of highly educated participants. Clinical trial identification: NCT03672331. Legal entity responsible for the study: Unicancer. Funding: European Commission and French National Cancer Institute. Disclosure: S. Delaloge: Financial Interests, Institutional, Advisory Board: AstraZeneca;Financial Interests, Institutional, Invited Speaker: Exact Sciences;Financial Interests, Institutional, Advisory Board: Novartis;Financial Interests, Institutional, Advisory Board: Pierre fabre;Financial Interests, Institutional, Advisory Board: Orion;Financial Interests, Institutional, Advisory Board: Sanofi;Financial Interests, Institutional, Advisory Board: Rappta;Financial Interests, Institutional, Advisory Board: Cellectis;Financial Interests, Institutional, Advisory Board: Isis/servier;Financial Interests, Institutional, Invited Speaker: Pfizer;Financial Interests, Institutional, Invited Speaker: Seagen;Financial Interests, Institutional, Invited Speaker: Lilly;Financial Interests, Institutional, Invited Speaker: AstraZeneca;Financial Interests, Institutional, Invited Speaker: MSD;Financial Interests, Institutional, Advisory Board, ad board: Besins Healthcare;Financial Interests, Institutional, Invited Speaker: Roche Genentech;Financial Interests, Institutional, Invited Speaker: BMS;Financial Interests, Institutional, Invited Speaker: Puma;Financial Interests, Institutional, Invited Speaker: AstraZeneca;Financial Interests, Institutional, Invited Speaker: Orion;Financial Interests, Institutional, Invited Speaker: Sanofi;Financial Interests, Institutional, Funding: GE;Financial Interests, Institutional, Invited Speaker: Pfizer;Financial Interests, Institutional, Invited Speaker, clinical research funding to my institution: Taiho;Non-Financial Interests, Invited Speaker, Société Française de Sénologie et Pathologie Mammaire: SFSPM. D. Keatley: Financial Interests, Personal, Advisory Board: Public Advisory Board of Heealth Data UK. E. Gauthier: Financial Interests, Personal, Stocks/Shares: Predilife;Financial Interests, Personal, Full or part-time Employment: Predilife. S. Michiels: Financial Interests, Personal, Advisory Role: IDDI;Financial Interests, Personal, Advisory Role: Amaris;Financial Interests, Personal, Advisory Role: Roche;Financial Interests, Personal, Advisory Role: Sensorion;Financial Interests, Personal, Advisory Role: Biophytis;Financial Interests, Personal, Advisory Role: Servier;Financial Interests, Personal, Advisory Role: Yuhan. All other authors have declared no conflicts of interest.

Surviving Debt and Survival Debt in Times of Lockdown

What are the consequences of the COVID-19 lockdown on household debt? Drawing on quantitative and qualitative data collected in rural Tamil Nadu, this paper highlights the massive risks of financial fragility. Quantitative data show a very high level of pre-COVID-19 debt, and the lockdown was accompanied by a large-scale suspension of repayments. At the same time, there was a halt to unsecured debt and an erosion of the trust that cements most transactions. Last, but not the least, the emergence of new forms of secured debt that seriously threaten household assets was observed. © 2022 Economic and Political Weekly. All rights reserved.

Sustained cancer clinical trial activity during the COVID-19 pandemic

Background: The COVID-19 pandemic deeply threatens the rigorous conduct of clinical trials, notably by delaying site initiation visits, patient enrolment, treatment administration, trial-associated procedures, and data monitoring. Unlike most other medical specialties, clinical trials are an integral part of patient care in oncology. Limiting access to clinical trials therefore results in a loss of chance for patients. Methods: In this retrospective single-center study, we collected clinical trial-specific items (including patient-related or trial management-related items) during the first pandemic wave (March– June 2020) and lockdown (March 17th-May 11th) at Gustave Roussy, and compared them to those of the same period in 2019. Results: In March 2020, 84 phase I (P1) and 210 phase II/III (P2/3) trials were open. During the first pandemic wave, 21 (25%) P1 and 20 (9%) P2/3 trials were temporarily halted, following a unilateral sponsor decision in virtually all cases;all but one were industry-sponsored. Despite this, all important metrics of the P1/2 trial activity remained similar to those of 2019, including the number of patients referred for inclusion (599 vs 620), inclusion consultations (215 vs 247), patients starting treatment (130 vs 130), Internal Review Board (IRB) submissions (14 vs 16), and site initiation visits (11 vs 15), all in 2020 vs 2019, respectively. The impact of the first lock-down was more marked on P2/3, with 152 patient inclusions (vs 346 in 2019), 125 randomizations (vs 278), 43 IRB submissions (vs 50) and 34 site initiation visits (vs 40). However, in parallel, 475 patients were included in three “COVID and cancer” trials. Among the 443 P1 and 2851 P2/3 patients, 198 and 628 COVID-19 PCR were performed internally, and five and 15 (2.5%) were positive, respectively. One patient with a community-based COVID-19 died after transfer in intensive care. Conclusions: Cancer clinical trials can, and must be maintained despite challenges brought by COVID-19. Sharing experiences and retrospectively evaluating the impact on patients’ safety and cancer-related outcomes will be critical to durably improve the clinical trials conduct and to anticipate at best challenges brought by future similar crises. Legal entity responsible for the study: Gustave Roussy. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.

Un modèle de micro-simulation à événements discrets pour estimer les impacts de l’épidémie de COVID-19 sur l’organisation des soins et la mortalité par cancer

Introduction L’épidémie de COVID-19 a bouleversé l’organisation des établissements de santé à travers la modification des flux de patients, la limitation des ressources médicales disponibles et la nécessité d’adapter les parcours de soins. Ce travail vise à quantifier ce potentiel impact sur les délais de diagnostic et de traitement, la saturation des ressources hospitalières et in fine la mortalité des patients atteints de cancer. Méthodes Les modèles de simulation à évènements discrets (DES) ont pour principe la modélisation d’entités qui empruntent diverses trajectoires sur lesquelles elles consomment des ressources en fonction de leurs caractéristiques. Afin de modéliser l’activité hospitalière, un DES a été développé pour modéliser la prise en charge des patients et l’utilisation de ressources hospitalières (volumes horaires des blocs chirurgicaux, radiothérapie, chimiothérapie, …) en fonction du type de cancer. Les flux patients ont été simulés à partir de données individuelles anonymisées issues du Programme de médicalisation des systèmes d’information (PMSI) de Gustave-Roussy. Les données historiques du PMSI de janvier 2018 à février 2020 ont permis la modélisation en séries temporelles (modèle ARIMA) des flux patients en l’absence de perturbation épidémique. La différence de ces flux avec les flux observés entre mars et octobre 2020 a informé le modèle sur les patients absents, pour lesquels deux scénarios de retour ont été envisagés : un retour massif à partir de novembre 2020 (retour rapide), ou un retour plus tardif à partir de mars 2021 (retour tardif). Le modèle DES prenant en compte ces flux simulés et la disponibilité attendue des ressources hospitalières a permis le calcul de retards individuels à la prise en charge. Le sur-risque de décès associé au retard de prise en charge par type de cancer, issu de la littérature, a été utilisé pour évaluer la surmortalité par cancer à cinq ans pour tous les patients se présentant à l’hôpital entre le début du premier confinement (mi-mars 2020), et la date à laquelle l’utilisation des ressources hospitalières reviendrait à son niveau habituel. Une analyse de sensibilité sur le taux d’utilisation réel des ressources hospitalières a été conduite. Résultats Le retour à une activité normale (absence de retards dans la venue des patients et dans l’utilisation des ressources) est prévu pour mai 2022 dans le scénario de retour rapide et pour juin 2022 dans le scénario de retour tardif (n∼13 000 patients) ;6 à 8 % des patients présentent un retard à la prise en charge supérieur à deux mois. Le nombre de décès supplémentaires à cinq ans est estimé à 88 pour le retour rapide, et à 145 pour le retour tardif, avec un impact accru pour les sarcomes, les cancers gynécologiques, les leucémies aiguës, les cancers ORL, du sein et du foie. Cela représente une surmortalité à cinq ans de 4 à 6,8 % chez les patients initialement attendus à l’hôpital en 2020, de 0,5 à 1,3 % pour ceux de 2021 et de 0,5 % pour ceux de 2022. Les analyses de sensibilité ont montré que des perturbations sur la disponibilité des ressources pouvaient entraîner une nouvelle hausse de cette surmortalité, de l’ordre de 2 à 18 %. Conclusion Les délais de diagnostic et de traitement des patients atteints de cancer pendant l’épidémie de COVID-19 ont un impact sur la survie des patients. Cet impact important nécessite d’organiser les soins de sorte que les diagnostics et les traitements des cancers restent accessibles et ne soient pas retardés lors de prochains épisodes épidémiques.