Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a second-line treatment with curative potential for leukemia patients. However, the prognosis of allo-HSCT patients with disease relapse or graft-versus-host disease (GvHD) is poor. CD4+ or CD8+ conventional T (Tconv) cells are critically involved in mediating anti-leukemic immune responses to prevent relapse and detrimental GvHD. Hence, treatment for one increases the risk of the other. Thus, therapeutic strategies that can address relapse and GvHD are considered the Holy Grail of allo-HSCT. CD3+CD4-CD8- double-negative T cells (DNTs) are unconventional mature T cells with potent anti-leukemia effects with "off-the-shelf" potential. A phase I clinical trial demonstrated the feasibility, safety, and potential efficacy of allogeneic DNT therapy for patients with relapsing acute myeloid leukemia (AML) post-allo-HSCT. Here, we studied the impact of DNTs on the anti-leukemic and GvHD-inducing activities of Tconv cells. DNTs synergized with Tconv cells to mediate superior anti-leukemic activity. Mechanistically, DNTs released soluble factors which activated and evoked potent anti-leukemic activities of Tconv cells. In contrast, DNTs suppressed GvHD-inducing activities of Tconv cells in a CD18-dependent manner by mediating cytotoxicity against proliferative Tconv cells. The seemingly opposite immunological activities of DNTs were dictated by the presence or absence of AML cells. Collectively, these results support the potential of DNTs as an adjuvant to allo-HSCT to address both disease relapse and GvHD.

Background: With the growing volume and complexity of laboratory repositories, it has become tedious to parse unstructured data into structured and tabulated formats for secondary uses such as decision support, quality assurance, and outcome analysis. However, advances in natural language processing (NLP) approaches have enabled efficient and automated extraction of clinically meaningful medical concepts from unstructured reports. Objective: In this study, we aimed to determine the feasibility of using the NLP model for information extraction as an alternative approach to a time-consuming and operationally resource-intensive handcrafted rule-based tool. Therefore, we sought to develop and evaluate a deep learning-based NLP model to derive knowledge and extract information from text-based laboratory reports sourced from a provincial laboratory repository system. Methods: The NLP model, a hierarchical multilabel classifier, was trained on a corpus of laboratory reports covering testing for 14 different respiratory viruses and viral subtypes. The corpus includes 87,500 unique laboratory reports annotated by 8 subject matter experts (SMEs). The classification task involved assigning the laboratory reports to labels at 2 levels: 24 fine-grained labels in level 1and 6 coarse-grained labels in level 2. A "label" also refers to the status of a specific virus or strain being tested or detected (eg, influenza A is detected). The model's performance stability and variation were analyzed across all labels in the classification task. Additionally, the model's generalizability was evaluated internally and externally on various test sets. Results: Overall, the NLP model performed well on internal, out-of-time (pre-COVID-19), and external (different laboratories) test sets with microaveraged F-1-scores >94% across all classes. Higher precision and recall scores with less variability were observed for the internal and pre-COVID-19 test sets. As expected, the model's performance varied across categories and virus types due to the imbalanced nature of the corpus and sample sizes per class. There were intrinsically fewer classes of viruses being detected than those tested; therefore, the model's performance (lowest F-1-score of 57%) was noticeably lower in the detected cases. Conclusions: We demonstrated that deep learning-based NLP models are promising solutions for information extraction from text-based laboratory reports. These approaches enable scalable, timely, and practical access to high-quality and encoded laboratory data if integrated into laboratory information system repositories.

<p>Table S1. Clinical information of the 46 AML patients who provided AML cells for in vitro or in vivo assays.</p>

Abstract Background Older adults are recommended to receive influenza vaccination annually, and many use statins. Statins have immunomodulatory properties that might modify influenza vaccine effectiveness (VE) and alter influenza infection risk. Methods Using the test-negative design and linked laboratory and health administrative databases in Ontario, Canada, we estimated VE against laboratory-confirmed influenza among community-dwelling statin users and nonusers aged ≥66 years during the 2010–2011 to 2018–2019 influenza seasons. We also estimated the odds ratio for influenza infection comparing statin users and nonusers by vaccination status. Results Among persons tested for influenza across the 9 seasons, 54 243 had continuous statin exposure before testing and 48 469 were deemed unexposed. The VE against laboratory-confirmed influenza was similar between statin users and nonusers (17% [95% confidence interval, 13%–20%] and 17% [13%–21%] respectively; test for interaction, P = .87). In both vaccinated and unvaccinated persons, statin users had higher odds of laboratory-confirmed influenza than nonusers (odds ratios for vaccinated and unvaccinated persons 1.15 [95% confidence interval, 1.10–1.21] and 1.15 [1.10–1.20], respectively). These findings were consistent by mean daily dose and statin type. VE did not differ between users and nonusers of other cardiovascular drugs, except for β-blockers. We did not observe that vaccinated and unvaccinated users of these drugs had increased odds of influenza, except for unvaccinated β-blocker users. Conclusions Influenza VE did not differ between statin users and nonusers. Statin use was associated with increased odds of laboratory-confirmed influenza in vaccinated and unvaccinated persons, but these associations might be affected by residual confounding.

Additional information on materials and methods used in this study

Dementia and mild cognitive impairment can be underrecognized in primary care practice and research. Free-text fields in electronic medical records (EMRs) are a rich source of information which might support increased detection and enable a better understanding of populations at risk of dementia. We used natural language processing (NLP) to identify dementia-related features in EMRs and compared the performance of supervised machine learning models to classify patients with dementia. We assembled a cohort of primary care patients aged 66 + years in Ontario, Canada, from EMR notes collected until December 2016: 526 with dementia and 44,148 without dementia. We identified dementia-related features by applying published lists, clinician input, and NLP with word embeddings to free-text progress and consult notes and organized features into thematic groups. Using machine learning models, we compared the performance of features to detect dementia, overall and during time periods relative to dementia case ascertainment in health administrative databases. Over 900 dementia-related features were identified and grouped into eight themes (including symptoms, social, function, cognition). Using notes from all time periods, LASSO had the best performance (F1 score: 77.2%, sensitivity: 71.5%, specificity: 99.8%). Model performance was poor when notes written before case ascertainment were included (F1 score: 14.4%, sensitivity: 8.3%, specificity 99.9%) but improved as later notes were added. While similar models may eventually improve recognition of cognitive issues and dementia in primary care EMRs, our findings suggest that further research is needed to identify which additional EMR components might be useful to promote early detection of dementia.

Figure S1. Characterization of ex vivo expanded healthy donor (HD) DNTs; Figure S2. Allogeneic DNTs induce dose- and time- dependent cytotoxicity against leukemic cells; Figure S3. Correlation between the susceptibility of AML patient blasts to DNT-mediated cytotoxicity and clinical features; Figure S4. Potency of anti-leukemic function mediated by allogeneic DNTs; Figure S5. Cytotoxic function of allogeneic DNTs on normal peripheral blood myeloid cells; Figure S6. NKp30, NKp44, and NKp46 are not involved in DNT-mediated killing of AML; Figure S7. Level of IFNγ production by DNTs corresponds with the level of cytotoxicity mediated by DNTs; Figure S8. DNAM-1 and NKG2D blocking abrogates IFNγ production by DNTs; Figure S9. IFNγ treatment does not affect the NKG2D and DNAM-1 ligand expression on normal PBMC; Figure S10. Cytotoxic activity of DNTs against leukemia cell lines derived from different types of leukemia and lymphoma; Figure S11. Effect of cryopreservation on the viability and anti-leukemic activity of ex vivo expanded DNTs.

Background: Pertussis is a reportable disease in many countries, but ascertainment bias has limited data accuracy. This study aims to validate pertussis data measures using a reference standard that incorporates different suspected case severities, allowing for the impact of case severity on accuracy and detection to be explored. Methods: We evaluated 25 pertussis detection algorithms in a primary care electronic medical record database between January 1, 1986 and December 30, 2016. We estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We used sensitivity analyses to explore areas of uncertainty and evaluated reasons for lack of detection. Results: The algorithm including all data measures achieved the highest sensitivity at 20.6%. Sensitivity increased to 100% after reclassifying symptom-only cases as non-cases, but the PPV remained low. Age at first episode was significantly associated with detection in half of the tested scenarios, and false negatives often had some history of immunization. Conclusions: Sensitivity improved by reclassifying symptom-only cases but remained low unless multiple data sources were used. Results demonstrate a trade-off between PPV and sensitivity. EMRs can enhance detection through patient history and clinical note data. It is essential to improve case identification of older individuals with vaccination history to reduce ascertainment bias.

Primary care is an important part of the help-seeking pathway for young people experiencing early psychosis, but sex differences in clinical presentation in these settings are unexplored. We aimed to identify sex differences in clinical presentation to primary care services in the 1-year period prior to a first diagnosis of psychotic disorder. We identified first-onset cases of non-affective psychotic disorder over a 10-year period (2005–2015) using health administrative data linked with electronic medical records (EMRs) from primary care (n = 465). Detailed information on encounters in the year prior to first diagnosis was abstracted, including psychiatric symptoms, other relevant behaviours, and diagnoses recorded by the family physician (FP). We used modified Poisson regression models to examine sex differences in the signs, symptoms, and diagnoses recorded by the FP, adjusting for various clinical and sociodemographic factors. Positive symptoms (PR = 0.76, 95%CI: 0.58, 0.98) and substance use (PR = 0.54, 95%CI: 0.40, 0.72) were less prevalent in the medical records of women. Visits by women were more likely to be assigned a diagnosis of depression or anxiety (PR = 1.18, 95%CI: 1.00, 1.38), personality disorder (PR = 5.49, 95%CI: 1.22, 24.62), psychological distress (PR = 11.29, 95%CI: 1.23, 103.91), and other mental or behavioral disorders (PR = 3.49, 95%CI: 1.14, 10.66) and less likely to be assigned a diagnosis of addiction (PR = 0.33, 95%CI: 0.13, 0.87). We identified evidence of sex differences in the clinical presentation of early psychosis and recorded diagnoses in the primary care EMR. Further research is needed to better understand sex differences in clinical presentation in the primary care context, which can facilitate better understanding, detection, and intervention for first-episode psychotic disorders.

SARS-CoV-2 variants of concern (VOC) are more transmissible and may have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax) and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2) VOC in Ontario, Canada, using a test-negative design study. We identified 682,071 symptomatic community-dwelling individuals who were tested for SARS-CoV-2, and 15,269 individuals with a COVID-19 hospitalization or death. Effectiveness against symptomatic infection ≥7 d after two doses was 89–92% against Alpha, 87% against Beta, 88% against Gamma, 82–89% against Beta/Gamma and 87–95% against Delta across vaccine products. The corresponding estimates ≥14 d after one dose were lower. Effectiveness estimates against hospitalization or death were similar to or higher than against symptomatic infection. Effectiveness against symptomatic infection was generally lower for older adults (≥60 years) than for younger adults (<60 years) for most of the VOC–vaccine combinations. Our findings suggest that jurisdictions facing vaccine supply constraints may benefit from delaying the second dose in younger individuals to more rapidly achieve greater overall population protection; however, older adults would likely benefit most from minimizing the delay in receiving the second dose to achieve adequate protection against VOC. Analysis of the effectiveness of three vaccines to protect against symptomatic SARS-CoV-2 infection and severe outcomes caused by Alpha, Beta, Gamma and Delta variants in Ontario, Canada, suggests that a single dose provides considerable protection, two doses provide even higher protection, and effectiveness against hospitalization or death is similar to or higher than against symptomatic infection.

Background There is limited population-based data on Neurofibromatosis type 1 (NF1) in North America. We aimed to develop and validate algorithms using administrative health data and electronic medical records (EMRs) to identify individuals with NF1 in Ontario, Canada. Methods We conducted an electronic free-text search of 15 commonly-used terms related to NF1 in the Electronic Medical Records Primary Care Database. Records were reviewed by two trained abstractors who classified them as confirmed, possible, and not NF1. An investigator with clinical expertise performed final NF1 classification. Patients were classified as confirmed if there was a documented diagnosis, meeting NIH criteria. Patients were classified as possible if (1) NF1 was recorded in the cumulative patient profile, but no clinical information to support the diagnosis; (2) only one criterion for diagnosis (e.g. child of confirmed case) but no further data to confirm or rule out. We tested different combinations of outpatient and inpatient billing codes, and applied a free-text search algorithm to identify NF1 cases in administrative data and EMRs, respectively. Results Of 273,440 eligible patients, 2,058 had one or more NF1 terms in their medical records. The terms “NF”, “café-au-lait”, or “sheath tumour” were constrained to appear in combination with another NF1 term. This resulted in 837 patients: 37 with possible and 71 with confirmed NF1. The population prevalence ranged from 1 in 3851 (confirmed NF1) to 1 in 2532 (possible and confirmed NF1). Billing code algorithms had poor performance, with overall low PPV (highest being 71%). The accuracy of the free-text EMR algorithm in identifying patients with NF1 was: sensitivity 85% (95% CI 74–92%), specificity 100% (95% CI 100–100%), positive predictive value 80% (95% CI 69–88%), negative predictive value 100% (95% CI 100–100%), and false positive rate 20% (95% CI 11–33%). Of false positives, 53% were possible NF1. Conclusions A free-text search algorithm within the EMR had high sensitivity, specificity and predictive values. Algorithms using billing codes had poor performance, likely due to the lack of NF-specific codes for outpatient visits. While NF1 ICD-9 and 10 codes are used for hospital admissions, only ~ 30% of confirmed NF1 cases had a hospitalization associated with an NF1 code.

PurposePertussis surveillance remains essential in Canada, but ascertainment bias limits the accuracy of surveillance data. Introducing other sources to improve detection has highlighted the importance of validation. However, challenges arise due to low prevalence, and oversampling suspected cases can introduce partial verification bias. The aim of this study was to build a reference standard for pertussis validation studies that provides adequate analytic precision and minimizes bias.MethodsWe used a stratified strategy to sample the reference standard from a primary care electronic medical record cohort. We incorporated abstractor notes into definite, possible, ruled-out, and no mention of pertussis classifications which were based on surveillance case definitions.ResultsWe abstracted eight hundred records from the cohort of 404,922. There were 208 (26%) definite and 261 (32.6%) possible prevalent pertussis cases. Classifications demonstrated a wide variety of case severities. Abstraction reliability was moderate to substantial based on Cohen's kappa and raw percent agreement.ConclusionsWhen conducting validation studies for pertussis and other low prevalence diseases, this stratified sampling strategy can be used to develop a reference standard using limited resources. This approach mitigates verification and spectrum bias while providing sufficient precision and incorporating a range of case severities.

Objective: Pertussis surveillance remains essential in Canada, but ascertainment bias limits the accuracy of surveillance data. Introducing other sources to improve detection has highlighted the importance of validation. However, challenges arise due to low prevalence, and oversampling suspected cases can introduce partial verification bias. The aim of this study was to build a reference standard for pertussis validation studies that provides adequate analytic precision and minimizes bias. Study Design and Setting: We used a stratified strategy to sample the reference standard from a primary care electronic medical record cohort, with the last 50% allocated to optimize precision using predicted cases from count models. We incorporated abstractor notes into definite, possible, ruled-out, and no mention of pertussis classifications.Results: We abstracted eight hundred records from the cohort of 404,922. There were 208 (26.0%) definite and 261 (32.6%) possible prevalent cases. Classifications demonstrated a wide variety of case severities. During optimization, the predicted width of 95% confidence intervals for sensitivity ranged from 12.4% to 32.8%. Conclusion: When conducting validation studies for low prevalence diseases like pertussis, this stratified sampling strategy can be used to develop a reference standard using limited resources. This approach mitigates verification bias while providing sufficient precision and incorporating a range of case severities.

Objectives: To estimate the effectiveness of BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and ChAdOx1 (AstraZeneca) vaccines against symptomatic SARS-CoV-2 infection and severe outcomes (COVID-19 hospitalization or death) caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) variants of concern (VOCs) during December 2020 to May 2021. Methods: We conducted a test-negative design study using linked population-wide vaccination, laboratory testing, and health administrative databases in Ontario, Canada. Results: Against symptomatic infection caused by Alpha, vaccine effectiveness with partial vaccination ([≥]14 days after dose 1) was higher for mRNA-1273 than BNT162b2 and ChAdOx1. Full vaccination ([≥]7 days after dose 2) increased vaccine effectiveness for BNT162b2 and mRNA-1273 against Alpha. Protection against symptomatic infection caused by Beta/Gamma was lower with partial vaccination for ChAdOx1 than mRNA-1273. Against Delta, vaccine effectiveness after partial vaccination tended to be lower than against Alpha for BNT162b2 and mRNA-1273, but was similar to Alpha for ChAdOx1. Full vaccination with BNT162b2 increased protection against Delta to levels comparable to Alpha and Beta/Gamma. Vaccine effectiveness against hospitalization or death caused by all studied VOCs was generally higher than for symptomatic infection after partial vaccination with all three vaccines. Conclusions: Our findings suggest that even a single dose of these 3 vaccine products provide good to excellent protection against symptomatic infection and severe outcomes caused by the 4 currently circulating variants of concern, and that 2 doses are likely to provide even higher protection.

Optimiser la réponse de la santé publique pour diminuer le fardeau de la COVID-19 nécessite la caractérisation de l’hétérogénéité du risque posé par la maladie à l’échelle de la population. Cependant, l’hétérogénéité du dépistage du SRAS-CoV-2 peut fausser les estimations selon le modèle d’étude analytique utilisé. Notre objectif était d’explorer les biais collisionneurs dans le cadre d’une vaste étude portant sur les déterminants de la maladie et d’évaluer les déterminants individuels, environnementaux et sociaux du dépistage et du diagnostic du SRAS-CoV-2 parmi les résidents de l’Ontario, au Canada. MÉTHODES: Nous avons exploré la présence potentielle de biais collisionneurs et caractérisé les déterminants individuels, environnementaux et sociaux de l’obtention d’un test de dépistage et d’un résultat positif à la présence de l’infection au SRAS-CoV-2 à l’aide d’analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivité en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilisé des études analytiques distinctes afin de comparer les prédicteurs pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que négatif, pour les personnes symptomatiques d’obtenir un résultat de test de dépistage positif plutôt que négatif et pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que de ne pas obtenir un résultat positif (c.-à-d., obtenir un résultat de test de dépistage négatif ou ne pas obtenir de test de dépistage). Nos analyses comprennent des tests de dépistage réalisés entre le 1er mars et le 20 juin 2020. RÉSULTATS: Sur 14 695 579 personnes, nous avons constaté que 758 691 d’entre elles ont passé un test de dépistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un résultat positif. Plus la probabilité d’obtenir un test de dépistage s’éloignait de zéro, plus la variabilité généralement observée dans la probabilité d’un diagnostic était grande parmi les modèles d’études analytiques, particulièrement en ce qui a trait aux facteurs individuels. Nous avons constaté que la variabilité dans l’obtention d’un test de dépistage était moins importante en fonction des déterminants sociaux dans l’ensemble des études analytiques. Les facteurs tels que le fait d’habiter dans une région ayant une plus haute densité des ménages (rapport de cotes corrigé 1,86; intervalle de confiance [IC] à 95 % 1,75–1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrigé 1,58; IC à 95 % 1,48–1,69), une population atteignant un plus faible niveau de scolarité (rapport de cotes corrigé 1,33; IC à 95 % 1,26–1,41) et une plus grande proportion d’immigrants récents (rapport de cotes corrigé 1,10; IC à 95 % 1,05–1,15), étaient systématiquement corrélés à une probabilité plus importante d’obtenir un diagnostic de SRAS-CoV-2, peu importe le modèle d’étude analytique employé. INTERPRÉTATION: Lorsque la capacité de dépister est limitée, nos résultats suggèrent que les facteurs de risque peuvent être estimés plus adéquatement en utilisant des comparateurs populationnels plutôt que des comparateurs de résultat négatif au test de dépistage. Optimiser la lutte contre la COVID-19 nécessite des investissements dans des interventions structurelles déployées de façon suffisante et adaptées à l’hétérogénéité des déterminants sociaux du risque, dont le surpeuplement des ménages, l’occupation professionnelle et le racisme structurel.

BACKGROUND: Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada. METHODS: We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020. RESULTS: Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design. INTERPRETATION: Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.

ABSTRACT SARS-CoV-2 variants of concern (VOC) are more transmissible and have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax), and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) VOCs in Ontario, Canada using a test-negative design study. Effectiveness against symptomatic infection ≥7 days after two doses was 89–92% against Alpha, 87% against Beta, 88% against Gamma, 82–89% against Beta/Gamma, and 87–95% against Delta across vaccine products. The corresponding estimates ≥14 days after one dose were lower. Effectiveness estimates against hospitalization or death were similar to, or higher than, against symptomatic infection. Effectiveness against symptomatic infection is generally lower for older adults (≥60 years) compared to younger adults (<60 years) for most of the VOC-vaccine combinations.

Acute myeloid leukemia (AML) remains a devastating disease in need of new therapies to improve patient survival. Targeted adoptive T-cell therapies have achieved impressive clinical outcomes in some B-cell leukemias and lymphomas but not in AML. Double-negative T cells (DNTs) effectively kill blast cells from the majority of AML patients and are now being tested in clinical trials. However, AML blasts obtained from ∼30% of patients show resistance to DNT-mediated cytotoxicity; the markers or mechanisms underlying this resistance have not been elucidated. Here, we used a targeted clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) screen to identify genes that cause susceptibility of AML cells to DNT therapy. Inactivation of the Spt-Ada-Gcn5-acetyltransferase (SAGA) deubiquitinating complex components sensitized AML cells to DNT-mediated cytotoxicity. In contrast, CD64 inactivation resulted in resistance to DNT-mediated cytotoxicity. Importantly, the level of CD64 expression correlated strongly with the sensitivity of AML cells to DNT treatment. Furthermore, the ectopic expression of CD64 overcame AML resistance to DNTs in vitro and in vivo. Altogether, our data demonstrate the utility of CRISPR/Cas9 screens to uncover mechanisms underlying the sensitivity to DNT therapy and suggest CD64 as a predictive marker for response in AML patients.

Contexte: Optimiser la reponse de la sante publique pour diminuer le fardeau de la COVID-19 necessite la caracterisation de l'heterogeneite du risque pose par la maladie a l'echelle de la population. Cependant, l'heterogeneite du depistage du SRAS-CoV-2 peut fausser les estimations selon le modele d'etude analytique utilise. Notre objectif etait d'explorer les biais collisionneurs dans le cadre d'une vaste etude portant sur les determinants de la maladie et d'evaluer les determinants individuels, environnementaux et sociaux du depistage et du diagnostic du SRAS-CoV-2 parmi les residents de l'Ontario, au Canada. Methodes: Nous avons explore la presence potentielle de biais collisionneurs et caracterise les determinants individuels, environnementaux et sociaux de l'obtention d'un test de depistage et d'un resultat positif a la presence de l'infection au SRAS-CoV-2 a l'aide d'analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivite en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilise des etudes analytiques distinctes afin de comparer les predicteurs pour les personnes d'obtenir un resultat de test de depistage positif plutot que negatif, pour les personnes symptomatiques d'obtenir un resultat de test de depistage positif plutot que negatif et pour les personnes d'obtenir un resultat de test de depistage positif plutot que de ne pas obtenir un resultat positif (c.-a-d., obtenir un resultat de test de depistage negatif ou ne pas obtenir de test de depistage). Nos analyses comprennent des tests de depistage realises entre le 1(er) mars et le 20 juin 2020. Resultats: Sur 14 695 579 personnes, nous avons constate que 758 691 d'entre elles ont passe un test de depistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un resultat positif. Plus la probabilite d'obtenir un test de depistage s'eloignait de zero, plus la variabilite generalement observee dans la probabilite d'un diagnostic etait grande parmi les modeles d'etudes analytiques, particulierement en ce qui a trait aux facteurs individuels. Nous avons constate que la variabilite dans l'obtention d'un test de depistage etait moins importante en fonction des determinants sociaux dans l'ensemble des etudes analytiques. Les facteurs tels que le fait d'habiter dans une region ayant une plus haute densite des menages (rapport de cotes corrige 1,86; intervalle de confiance [IC] a 95 % 1,75-1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrige 1,58; IC a 95 % 1,48-1,69), une population atteignant un plus faible niveau de scolarite (rapport de cotes corrige 1,33; IC a 95 % 1,26-1,41) et une plus grande proportion d'immigrants recents (rapport de cotes corrige 1,10; IC a 95 % 1,05-1,15), etaient systematiquement correles a une probabilite plus importante d'obtenir un diagnostic de SRAS-CoV-2, peu importe le modele d'etude analytique employe. Interpretation: Lorsque la capacite de depister est limitee, nos resultats suggerent que les facteurs de risque peuvent etre estimes plus adequatement en utilisant des comparateurs populationnels plutot que des comparateurs de resultat negatif au test de depistage. Optimiser la lutte contre la COVID-19 necessite des investissements dans des interventions structurelles deployees de facon suffisante et adaptees a l'heterogeneite des determinants sociaux du risque, dont le surpeuplement des menages, l'occupation professionnelle et le racisme structurel.

Background: We estimated the effectiveness of BNT162b2 and mRNA-1273 vaccines among residents of Ontario, Canada, where a policy to use an up to 16-week interval between doses was adopted in March 2021.Methods: We conducted a test-negative design study using linked province-wide laboratory, vaccination, and health administrative datasets. We included symptomatic individuals tested for SARS-CoV-2 by RT-PCR between 14 December 2020 and 19 April 2021. Study outcomes included symptomatic infection and associated severe outcomes (hospitalization or death). We estimated adjusted vaccine effectiveness (aVE) using multivariable logistic regression.Findings: Among 324,033 symptomatic tested individuals, 53,270 (16·4%) were positive for SARS-CoV-2 and 21,272 (6·6%) had received ≥1 dose of mRNA vaccine. Among test-positive cases, 2,479 (4·7%) had a severe outcome. aVE against symptomatic infection ≥14 days after receiving only 1 dose was 60% (95%CI, 57–64%), increasing from 48% (95%CI, 41–54%) at 14–20 days after the first dose to 71% (95%CI, 63–78%) at 35–41 days. aVE ≥7 days after receiving 2 doses was 91% (95%CI, 89–93%). Against severe outcomes, aVE ≥14 days after receiving 1 dose was 70% (95%CI, 60–77%) and aVE ≥7 days after receiving 2 doses was 98% (95%CI, 88–100%). We observed lower aVE against both outcomes after receiving 1 dose for adults aged ≥70 years, but aVE estimates for older adults were comparable to younger adults after 28 days. After 2 doses, we observed high aVE against E484K-positive variants.Interpretation: Our findings suggest that 2 doses of BNT162b2 and mRNA-1273 vaccines are highly effective against both symptomatic infection and associated severe outcomes for all circulating variants, with effectiveness lower after only a single dose, particularly for older adults shortly after the first dose.Funding Information: Canadian Institutes of Health Research, Public Health Agency of Canada, Ontario Ministries of Health and Long-Term Care.Declaration of Interests: KW is CEO of CANImmunize and serves on the data safety board for the Medicago COVID-19 vaccine trial. SMM has received unrestricted research grants from Merck, GlaxoSmithKline, Sanofi Pasteur, Pfizer, and Roche-Assurex for unrelated studies. SMM has received fees as an advisory board member for GlaxoSmithKline, Merck, Pfizer, Sanofi Pasteur, and Seqirus. CHR has received an unrestricted research grant from Pfizer for an unrelated study. The other authors declare no conflicts of interest.Ethics Approval Statement: ICES is a prescribed entity under Ontario's Personal Health Information Protection Act (PHIPA). Section 45 of PHIPA authorizes ICES to collect personal health information, without consent, for the purpose of analysis or compiling statistical information with respect to the management of, evaluation or monitoring of, the allocation of resources to or planning for all or part of the health system. Projects that use data collected by ICES under section 45 of PHIPA, and use no other data, are exempt from REB review. The use of the data in this project is authorized under section 45 and approved by ICES' Privacy and Legal Office.