BMJ medicine最新文献

The T cell memory response is a crucial component of adaptive immunity responsible for limiting or preventing viral reinfection. T cell memory after infection with the SARS-CoV-2 virus or vaccination is broad, and spans multiple viral proteins and epitopes, about 20 in each individual. So far the T cell memory response is long lasting and provides a high level of cross reactivity and hence resistance to viral escape by variants of the SARS-CoV-2 virus, such as the omicron variant. All current vaccine regimens tested produce robust T cell memory responses, and heterologous regimens will probably enhance protective responses through increased breadth. T cell memory could have a major role in protecting against severe covid-19 disease through rapid viral clearance and early presentation of epitopes, and the presence of cross reactive T cells might enhance this protection. T cell memory is likely to provide ongoing protection against admission to hospital and death, and the development of a pan-coronovirus vaccine might future proof against new pandemic strains.

Objective: To evaluate the efficacy of covid-19 convalescent plasma to treat patients admitted to hospital for moderate covid-19 disease with or without underlying immunodeficiency (CORIPLASM trial).

Design: Open label, randomised clinical trial.

Setting: CORIMUNO-19 cohort (publicly supported platform of open label, randomised controlled trials of immune modulatory drugs in patients admitted to hospital with moderate or severe covid-19 disease) based on 19 university and general hospitals across France, from 16 April 2020 to 21 April 2021.

Participants: 120 adults (n=60 in the covid-19 convalescent plasma group, n=60 in the usual care group) admitted to hospital with a positive SARS-CoV2 test result, duration of symptoms <9 days, and World Health Organization score of 4 or 5. 49 patients (n=22, n=27) had underlying immunosuppression.

Interventions: Open label randomisation to usual care or four units (200-220 mL/unit, 2 units/day over two consecutive days) of covid-19 convalescent plasma with a seroneutralisation titre >40.

Main outcome measures: Primary outcomes were proportion of patients with a WHO Clinical Progression Scale score of ≥6 on the 10 point scale on day 4 (higher values indicate a worse outcome), and survival without assisted ventilation or additional immunomodulatory treatment by day 14. Secondary outcomes were changes in WHO Clinical Progression Scale scores, overall survival, time to discharge, and time to end of dependence on oxygen supply. Predefined subgroups analyses included immunosuppression status, duration of symptoms before randomisation, and use of steroids.

Results: 120 patients were recruited and assigned to covid-19 convalescent plasma (n=60) or usual care (n=60), including 22 (covid-19 convalescent plasma) and 27 (usual care) patients who were immunocompromised. 13 (22%) patients who received convalescent plasma had a WHO Clinical Progression Scale score of ≥6 at day 4 versus eight (13%) patients who received usual care (adjusted odds ratio 1.88, 95% credible interval 0.71 to 5.24). By day 14, 19 (31.6%) patients in the convalescent plasma group and 20 (33.3%) patients in the usual care group needed ventilation, additional immunomodulatory treatment, or had died. For cumulative incidence of death, three (5%) patients in the convalescent plasma group and eight (13%) in the usual care group died by day 14 (adjusted hazard ratio 0.40, 95% confidence interval 0.10 to 1.53), and seven (12%) patients in the convalescent plasma group and 12 (20%) in the usual care group by day 28 (adjusted hazard ratio 0.51, 0.20 to 1.32). In a subgroup analysis performed in patients who were immunocompromised, transfusion of covid-19 convalescent plasma was associated with mortality (hazard ratio 0.39, 95% confidence interval 0.14 to 1.10).

Conclusions: In th

Objective: To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification.

Design: Secondary analysis of data in the Polygenic Score Catalog.

Setting: Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification.

Participants: Individuals contributing to the published studies in the Polygenic Score Catalog.

Main outcome measures: Detection rate for a 5% false positive rate (DR₅) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples.

Results: For performance in population screening, median DR₅ for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR₅ was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases.

Conclusion: Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.

Polycystic ovary syndrome is characterised by excessive levels of androgens and ovulatory dysfunction, and is a common endocrine disorder in women of reproductive age. Polycystic ovary syndrome arises as a result of polygenic susceptibility in combination with environmental influences that might include epigenetic alterations and in utero programming. In addition to the well recognised clinical manifestations of hyperandrogenism and ovulatory dysfunction, women with polycystic ovary syndrome have an increased risk of adverse mental health outcomes, pregnancy complications, and cardiometabolic disease. Unlicensed treatments have limited efficacy, mostly because drug development has been hampered by an incomplete understanding of the underlying pathophysiological processes. Advances in genetics, metabolomics, and adipocyte biology have improved our understanding of key changes in neuroendocrine, enteroendocrine, and steroidogenic pathways, including increased gonadotrophin releasing hormone pulsatility, androgen excess, insulin resistance, and changes in the gut microbiome. Many patients with polycystic ovary syndrome have high levels of 11-oxygenated androgens, with high androgenic potency, that might mediate metabolic risk. These advances have prompted the development of new treatments, including those that target the neurokinin-kisspeptin axis upstream of gonadotrophin releasing hormone, with the potential to lessen adverse clinical sequelae and improve patient outcomes.

Objective: To assess the uptake of second line antihyperglycaemic drugs among patients with type 2 diabetes mellitus who are receiving metformin.

Design: Federated pharmacoepidemiological evaluation in LEGEND-T2DM.

Setting: 10 US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics network in eight countries from 2011 to the end of 2021.

Participants: 4.8 million patients (≥18 years) across US and non-US based databases with type 2 diabetes mellitus who had received metformin monotherapy and had initiated second line treatments.

Exposure: The exposure used to evaluate each database was calendar year trends, with the years in the study that were specific to each cohort.

Main outcomes measures: The outcome was the incidence of second line antihyperglycaemic drug use (ie, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, and sulfonylureas) among individuals who were already receiving treatment with metformin. The relative drug class level uptake across cardiovascular risk groups was also evaluated.

Results: 4.6 million patients were identified in US databases, 61 382 from Spain, 32 442 from Germany, 25 173 from the UK, 13 270 from France, 5580 from Scotland, 4614 from Hong Kong, and 2322 from Australia. During 2011-21, the combined proportional initiation of the cardioprotective antihyperglycaemic drugs (glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors) increased across all data sources, with the combined initiation of these drugs as second line drugs in 2021 ranging from 35.2% to 68.2% in the US databases, 15.4% in France, 34.7% in Spain, 50.1% in Germany, and 54.8% in Scotland. From 2016 to 2021, in some US and non-US databases, uptake of glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors increased more significantly among populations with no cardiovascular disease compared with patients with established cardiovascular disease. No data source provided evidence of a greater increase in the uptake of these two drug classes in populations with cardiovascular disease compared with no cardiovascular disease.

Conclusions: Despite the increase in overall uptake of cardioprotective antihyperglycaemic drugs as second line treatments for type 2 diabetes mellitus, their uptake was lower in patients with cardiovascular disease than in people with no cardiovascular disease over the past decade. A strategy is needed to ensure that medication use is concordant with guideline recommendations to improve outcomes of patients with type 2 diabetes mellitus.