dataesr/scientific-paragraphs-categorization huggingface dataset:
Regular CPAP treatment (>4 hours/night) was not associated with a lower rate of MACEs, but cluster analysis identified identified a subgroup that was younger, more obese, and had more severe OSA (higher AHI and TST90) in whom CPAP therapy reduced the risk of MACE. The group of Prof. Frederic Gagnadoux analysed the association between CV outcomes and quartiles of average daily CPAP use using data from the Pays de la Loire Sleep Cohort and the French administrative healthcare database. They concluded that there was a dose-response relationship between CPAP adherence and the incidence of MACEs in OSA. In particular, they observed a reduction in morbidity and mortality of CV diseases in patients who used CPAP for more than 6 hours per day  [7]. This association was stronger in sleepy OSA patients without established cardiovascular disease Another paper that was discussed in this "Year in review" session evaluated the association between pulse wave amplitude drops (PWAD) index and incident or recurrent cardiovascular events in three prospective cohorts: HypnoLaus (general population), ISAACC (acute coronary syndrome with OSA), and the Pays de la Loire Sleep Cohort (PLSC, OSA cohort)  [8].
The relationship of demographic characteristics, comorbid diseases, and sleep-related health issues with OSA phenotypes and their effects on positive airway pressure (PAP) adherence were evaluated in the study, which followed these three phenotypes receiving PAP therapy for two years, and it was determined that OSA treatment response and adherence were related to the initial phenotype. The major improvement in daytime and nocturnal OSA symptoms was in the excessive sleepy patient group  [34]. The European Sleep Apnea Database (ESADA) was used to assess responses to PAP treatment change in apnoea severity and ESS in relation to baseline patient clusters and at short-and long-term followup. In this large, multinational study where seven distinct clusters were identified, daytime sleepiness response to PAP treatment varied between clusters, although there was a homogeneous AHI reduction.
Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. Final overall survival (OS) in SOPHIA (ClinicalTrials. gov identifier: NCT02492711), a study of margetuximab versus trastuzumab, both with chemotherapy, in patients with previously treated human epidermal growth factor receptor 2-positive advanced breast cancer, is reported with updated safety. Overall, 536 patients in the intention-to-treat population were randomly assigned to margetuximab (15 mg/kg intravenously once every 3 weeks; n 5 266) plus chemotherapy or trastuzumab (6 mg/kg intravenously once every 3 weeks after a loading dose of 8 mg/kg; n 5 270) plus chemotherapy.
INTRODUCTION Margetuximab-cmkb is an Fc-engineered anti-human epidermal growth factor receptor 2 (anti-HER2) immunoglobulin G monoclonal antibody that targets the same epitope as trastuzumab, with similar antiproliferative effects. 1, 2 [3] [4]  Primary analysis of progression-free survival (PFS) by central review of the phase 3 study SOPHIA (ClinicalTrials. gov identifier: NCT02492711)  5  led to the US Food and Drug Administration approval of margetuximab with chemotherapy in patients with HER21 metastatic breast cancer (BC) who have received $ 2 prior anti-HER2 regimens, at least one of which was for metastatic disease. 6 Here, we report the final overall survival (OS) analysis after 385 deaths, with updated safety information.
Studies of margetuximab in patients with HER21 BC with different CD16A allelic variants are warranted, including MARGOT (ClinicalTrials. gov identifier: NCT04425018), a randomized phase 2, neoadjuvant investigator-initiated study on the efficacy of margetuximab versus trastuzu- mab (both plus pertuzumab and paclitaxel) in patients with stage II-III HER21 BC carrying the CD16A-158F low- affinity allele. AFFILIATIONS 2 Cancer Research Institute, Seoul National University College of 1 University of California San Francisco Helen Diller Family Medicine, Seoul National University Hospital, Seoul, South Korea Comprehensive Cancer Center, San Francisco, CA.
Acknowledgments We would like to thank  Dr Bravi Serge  ( Department of Aesthetic and Plastic Surgery, Clinique des Cèdres, Cornebarrieu, France ) and  Dr Laurent Soubirac  ( Department of Aesthetic and Plastic Surgery, Medipole, Toulouse, France ) for supplying liposuction samples. We also thank  Eddy Magdeleine  for his contribution to the study (Icelltis company).
8%) of the 16 patients receiving RVd-DARA achieved a stringent CR as best response at last follow-up. 67  Additionally, the phase III COLUMBA RRMM trial has demonstrated non-inferiority of SC versus IV daratumumab, with an improved safety profile. 68  The phase II PLEIADES study examined the addition of SC daratumumab to standard-of-care regimens and found that SC daratumumab had comparable efficacy to IV daratumumab (≥VGPR of 71. 6% for RVd-DARA, ORR of 88. 1% for VMP-DARA, ORR of 90. 8% for Rd-DARA), with a median infusion duration of only 5 minutes and a low rate (≤9%) of infusion-related reactions. 69  The ongoing phase III NDMM studies MMY3019 (NCT03652064) and PERSEUS (NCT03710603) are evaluating RVd-DARA versus RVd using SC daratumumab in patients not planned to undergo ASCT and in TE patients, Haematologica | 108 November 2023 respectively.
Of note, the PERSEUS study used a regimen of oral lenalidomide 25 mg on days 1-21 and oral dexamethasone 40 mg on days 1-4 and days 9-12 of each 28-day induction cycle. Additionally, the ongoing phase II MMY2040 study is evaluating multiple daratumumab-containing regimens (including RVd-DARA) using the SC formulation (NCT03412565). In the phase I portion of SWOG S1211, elotuzumab + RVd demonstrated limited additive toxicity to RVd alone. 70  However, in the randomized phase II portion in high-risk NDMM, elotuzumab + RVd did not significantly improve patients' outcomes compared to RVd alone (ORR=83% vs. 88%; median PFS, 31 vs. 34 months). 71  This finding was supported in a follow-up analysis of RVd + elotuzumab versus RVd in SWOG-1211, with no improvement in median PFS (29 vs. 34 months) or OS (NR vs.
68 months) observed with a median follow-up of 6 years. 71  Another phase II trial of patients with TE NDMM demonstrated an ORR (after 4 cycles) of 82. 5%, with 55. 0% of patients achieving ≥VGPR. 72  However, 50% of patients experienced infections, including one grade 5 sepsis. In the phase III GMMG HD6 trial, four induction cycles of elotuzumab + RVd produced similar response outcomes as RVd alone (ORR, 82. 4% vs. 85. 6%; ≥VGPR, 58. 3% vs. 54. 0%). 73  Isatuximab + RVd was well tolerated in a phase I study and extremely active,  74  with phase I (NCT02513186), phase II/III (UK-MRA Myeloma XV RADAR [2019-001258-25]), and phase III (GMMG-HD7 [NCT03617731] and IMROZ [NCT03319667]) NDMM clinical trials ongoing. 75  Notably, the combination of panobinostat + RVd demonstrated activity and tolerability in a phase Ib study of patients with RRMM  76  and favorable efficacy in a phase Ib study of TE NDMM patients.
Moreover, the excellent activity of RVd has been confirmed outside of the clinical trial setting. 65  The RVD 1000 study, a database cohort study of 1,000 patients with NDMM who received RVd induction ± ASCT and risk-adapted maintenance, reported an ORR of 97. 1% after induction (≥VGPR, 67. 6%; ≥CR, 35. 9%), a median PFS of 65. 0 months, and a median OS of 126. 6 months, demonstrating the substantial long-term benefit of RVd. The large size of the study enables subanalyses, including for standard-versus high-risk cytogenetics (median PFS, 76. 5 vs. 40. 3 months; median OS, NR vs. 78. 2 months, respectively). In the context of the TE NDMM population, the recent results of DETERMINATION, with its relative maturity of follow-up, provide insights into the benefit of RVd in different populations and validate the tailoring of treatment in each individual patient, based upon the outcomes reported.
VDCR) → BORT Neuropathy: 17% maintenance ORR (end of consolidation): Grade 3/4 AE 97% (during RVd induction or IFM 2008 30 (NCT01206205) ≥VGPR (end of consolidation): consolidation) Neutropenia: 35% 3 × 21-day cycles of N=31 87% 3-yr PFS rate: 77% Thrombocytopenia: 13% RVd → ASCT → 2 cycles of RVd consolidation → LEN mainte-nance (+ BORT if patient had high-risk features) TE patients ORR (best response at any time): 100% 3-yr OS rate: 100% Grade 3/4 AE (reported at any time) Neutropenia: 65% ≥VGPR Thrombocytopenia: 19% (best response at any time): 84% No grade 3/4 neuropathy Grade ≥3 related AE CTRIAL-IE (ICORG) 13-17 33 ORR (after 4 cycles of RVd): (NCT02219178) 4 × 21-day cycles of RVd → (ASCT or 4 more cycles of RVd) N=42 TE or TNE patients 92. 5% c ≥VGPR (after 4 cycles of induction): Not reported Thrombocytopenia: 16.
7% Fatigue: 11. 9% Neutropenia: 9. 5% PN: 4. 8% → LEN maintenance 62. 5% c No grade 4 PN RVd Lite 31 Grade ≥3 TEAE (NCT01782963) 9 × 35-day cycles of RVd Lite N=50 ORR (after 4 cycles of RVd Lite): 86% Median PFS: 35. 1 mths Hypophosphatemia: 34% Fatigue: 16% → 6 × 28-day cycles of LEN + BORT consolidation → LEN TNE patients ≥VGPR (after 4 cycles of RVd Lite): 66% Median OS: NR Neutropenia: 14% PN: 2% maintenance Thrombocytopenia: 2% Grade ≥3 AE in patients FMG-MM02 32 who received (NCT01790737) ORR (best response at any 1-/2-/3-yr PFS rates: RVd induction (N=78) N=80 time): 89% 78%/67%/52% 3 × 21-day cycles of RVd → Neutropenia: 24% (CY + FIL mobilization vs. FIL TE patients ≥VGPR (best response at any 1-/2-/3-yr OS rates: Infections: 23% d mobilization) → ASCT → LEN time): 68% 96%/90%/83% Febrile neutropenia: 22% maintenance Thrombocytopenia: 14% PN: 3% Continued on following page.
AE reported with RVd are generally consistent with the Study Population Response PFS and OS Selected safety findings ORR (after induction): 83. 4% ≥VGPR (after induction): PETHEMA/ GEM2012 49 (NCT01916252) N=458 66. 6% ORR (after ASCT): 81. 2% Grade 3/4 AE through induction 6 × 28-day cycles of RVd → ASCT (IV busulfan + MEL) vs. ASCT (MEL) → 2 × 28-day cy-cles → RVd consolidation TE patients ≥VGPR (after ASCT): 75. 1% ORR (after consolidation): 80. 6% Median PFS: NR Neutropenia: 12. 9% Thrombocytopenia: 6. 3% Infection: 9. 2% PN: 3. 9% h ≥VGPR (after consolidation): 75. 5% N=1087 ENDURANCE (E1A11) 40 (NCT01863550) RVd: N=542 (N=527 for ORR, safety) 12 × 21-day cycles of RVd vs. 9 KRd: N=545 (N=526 for × 28-day cycles of KRd → LEN ORR, safety) maintenance × 2 years vs. LEN maintenance until PD Patients not planned for early ASCT a Due to differences in study design and procedures, cross-trial comparisons must be interpreted with caution.
Data collection procedures As this study uses a convergent parallel mixed-method design  [39] , quantitative and qualitative data will be collected at the same time from each cluster considered a case. In accordance with the stepped wedge design, the measurements will be carried out simultaneously in all sites of the same group during the pre-intervention period (one to two measurements depending on the cluster), once at the end of the intervention period and once at the 12th month post-intervention (Fig. 2 ). There will be no quantitative data collected during the intervention delivery period. Resident quantitative data will be retrieved using PICT and a subset of InterRAI-PC scales. Dedicated nurses with experience in palliative care will serve as research assistants after receiving training on the use of the above tools and the multidimensional evaluation approach.
They will register data in the RAisoft database. To collect descriptive and explanatory variables at the LTCF level, our research team developed an organizational questionnaire with two parts: (i) LTCF characteristics and functionalities: size and skill set of human resources, coordination with other community and hospital services in palliative care; and (ii) sociodemographic and medical characteristics, overall death rate of residents at the entire site. To complement the tools used to measure outcomes, the research team developed a structured checklist of indicators to assess retrospectively and prospectively the accessibility and quality of care provided to residents with palliative care needs. Trained research assistants will retrospectively review the files of the residents for six months before the pre-implementation period and throughout the study, as well as prospectively followup with prospective residents with palliative care needs.
Items related to consideration of residents' needs and preferences, symptom management, resident care pathway and health service use will be checked. Qualitative data will be collected continuously throughout the study duration. We will use a triangulation approach to data collection: individual interviews, focus groups, and participant observations, from multiple data sources. Individual in-depth semi-structured interviews will be conducted during the pre-and post-implementation phases with professionals and managers, informal caregivers, and residents from each site, as well as with specialised palliative support teams affiliated with the participating LTCF. In addition, focus group discussions with various healthcare professionals involved in the direct care of residents (nurses, nurse assistants, psychologists, physiotherapists, occupational therapists) from nine purposively selected cases will be conducted.
Interview guides specific to each group of participants will serve as data collection tools. Four themes will be explored throughout the interviews and focus groups: current practices, palliative care perceptions, quality of life at work, and barriers and facilitators of the implementation of early integrated palliative care. A researcher trained in qualitative research will conduct the individual interviews and focus groups. Participant observations will be carried out throughout different periods of study. An observation guide was developed to collect information during the observation of care situations in LTCF. Information will be collected on several items at each LTCF, including usual palliative care practices, level of quality of routine service, processes, structural characteristics, organizational culture and professional interactions, and external factors such as the exiting of support teams in palliative care services provision and the territorial provision/organisation of palliative care.
Quantitative analysis The quantitative data will be analysed using R. Statistical analysis and will be performed after a blind review of data quality issues and a database "freeze. " Due to the sequence of interventions, the analysis cannot be carried out in a blinded fashion. A patient flow chart will be set up according to the CONSORT extension recommendations for stepped wedge design  [61]. Main analysis will be performed on all included residents following the intent-to-treat principle and according to the role assigned to each period (usual care in the pre-intervention period versus experimental care in the post-intervention period) regardless of whether palliative care was implemented.
Descriptive analysis The descriptive analysis will summarize baseline clinical characteristics of the study cohort. Descriptive statistics will be reported as means and medians, standard deviations, and interquartile ranges. The nominal data will be reported as percentages with two-sided 95% confidence intervals. The proportions of missing data will be calculated. Participant characteristics (eligibility criteria, demographics data at inclusion) will be described and compared by setting and reported without comparison by period.
Primary outcome analysis The data analysis will be based on the comparison of data collected during pre-intervention versus postintervention periods. The three primary criteria will be tested according to a hierarchical procedure: identification sensitivity, access, and optimal timing from a fixed sequence procedure; constructed using a pre-specified sequence of hypotheses; and endpoints ordered according to their importance  [62]. All tests will be performed at the 0. 05 level following the pre-specified order. Once one hypothesis is tested and the results indicate it is not significant, all subsequent tests will not be performed. The statistical model will take into account the nonindependence of the observations, as multiple evaluations may concern the same resident across time due to the use of open cohorts and several residents are included from the same LTCF.
Integrative analysis The qualitative and quantitative analyses will be completed with an integrative analysis that uses intra-and inter-cases to identify similarities and differences. This approach will enrich the understanding of any internal and external patterns and variances identified in each case. The integration of qualitative and quantitative data will be carried out at each stage of analysis to perform an integrative analysis and interpretation. The results from the qualitative study will be triangulated with the results from the quantitative study, according to the research question being addressed, and will determine the integrative framework and different types of data that will be used and brought together in the analysis.
Ethics approval and informed consent Ethics approval for the conduct of this study was granted by the French Committee of Protection of Person (CPP), approval number 2020. 09. 06 bis 20. 07. 31. 64318. All participants (LTCF residents, family caregivers, and professionals) will be required to provide their informed consent in writing before their inclusion in the study. For residents who are unable to provide informed consent, this will be obtained from their legal representatives. Participant confidentiality will be ensured using codes and pseudonyms. De-identified data will be stored in protected computers and dedicated locked space. The use of databases and data processing are implemented in accordance with European regulations (General Data Protection Regulation -GDPR dated April 27, 2016).
Acknowledgements The authors of this article sincerely thank the funders of this study cited above and the scientific committee members for their valuable scientific support. We are also grateful for the support of the directors and staff from investigator centre partners:  Maison Médicale Jeanne Garnier ,  Centre Hospitalier d' Avignon , and  Maison de santé Marie Galène. We would also like to thank all residents, their families, and the professionals from the LTCF and other palliative care services ( EMSP, Réseau de santé, HAD ) who participated in our pilot study or the current study. We acknowledge the contribution of all members of  PADI-Palli team  involved in this study.
Funding: This work was supported by  Agena Bioscience (Hamburg, Germany ) within the scope of the  CANCER-ID  consortium, which has received support from the  Innovative Medicines Initiative (IMI) Joint Undertaking  under grant agreement no. 115749. Additional funding was received for  Bio-Rad  (Digital Biology Center,  Pleasanton, CA, USA ) by E. S. The funding had no role in the design of the study (other than the multicenter evaluation study), in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.
Acknowledgments This work was developed as part of a workshop funded by the  European Union Research  and  Innovation programme Horizon 2020  ( INFRAFRONTIER2020- Grant Agreement Number  730879 ) and by the  Healthy Lifespan Institute. L. N. is supported in part by  ASAP-000592. H. M. is supported by the  National Institute for Health and Care Research (NIHR) Sheffield Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the  National Health Service  (NHS), the  NIHR  or the  Department of Health and Social Care  (DHSC). L. -E. T. is supported by  Aligning Science Across Parkinson's (ASAP) , the  Krembil Foundation, Brain Canada , the  Canadian Institutes for Health Research (CIHR) , and the  Henri and Berenice Kaufmann foundation. E. R. is supported in part by the  Pittsburgh Pepper Center  ( P30 AG024827 ) and  Michael J Fox Foundation (MJFF).
Although promising, such non-intrusive AS profiling may be applied to other team-sport datasets that may include competitive sessions in order to provide sport-specific standards  [17]. Recently Clavel et al. [18]  demonstrated a nearly perfect correlation between radar and GPS-derived force-velocity variables. This study indicated that the GPS device is a valid, reliable, and time-effective alternative to radar for force-velocity assessment. Another major improvement would be to provide an error of measurement on A0 and S0 variables for each training type (e. g. , speed vs. scrimmage) and game, a major component to improve any decision-making process  [19]. Furthermore, the increasing volume of data now calls for an automatized development of algorithms for fast and accurate data processing, possibly through open-source repositories.
Data sample Forty-nine male rugby union players (mean ± SD; age: 27. 2 ± 5. 9 yr, height: 184. 2 ± 8. 0 cm, weight: 99. 6 ± 17. 1 kg) belonging to a French second division (ProD2) squad (ten first rows, seven second rows, ten third rows, three half scrums, two half backs, three centers, seven wings, three backs) were enroled. Over a 5-months period (i. e. , from Febrary 5 th to June 7 th 2021), they carried a global positioning system (GPS) sensor (Catapult Vector X7, Firmware: 8. 1. 0, Melbourne, Australia) sampled at 10 Hz during training sessions and games. According to the manufacturer guidelines and methodological considerations on minimum effort duration to quantify high-intensity efforts using GPS  [24] , acceleration and speed were identified only when effort duration exceeded a threshold of 0.
4 s. Acceleration data were derived from speed data with a time interval (referred in the software as Smoothing Filter Width) of 0. 2 s. Of the forty-nine players, two first rows and two centers were excluded from the study, due to long-term absence. Raw GPS data from 51 trainings (i. e. , 3-4 sessions per week including speed session, specific forwards or backs trainings, scrimmage session or lineout session), 11 official games (i. e. , one per week), and other sessions representing a dataset of 61. 5 million positions, speed and accelerations, were analyzed.
Outlier points' identification Before considering the relationship between maximal acceleration and maximal speed  [16] , outlier points (i. e. , artefacts or measurement errors) from GPS data were identified according to the distribution of theoretical maximal velocity (μV, σV) and theoretical maximal force (μF, σF), considered as norms in rugby union  [23]. By applying the 3σ-rule  [25] , an acceleration greater than μF + 3σF or a velocity greater than μV +3σV were considered unlikely. The force-velocity relationship being close to a linear relation, any value above the line formed by the y-intercept of μF + 3σF and the x-intercept of μV +3σV were also considered unlikely and therefore discarded. These values were counted for each session. Above 15 unlikely values (corresponding to 1. 5 s of consecutive improbable values), all player's data was dropped out for that session (Figure  1 ; black points).