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Enregistrement W4320519460 · doi:10.1016/j.lana.2023.100445

Breakthrough SARS-CoV-2 infections among patients with cancer following two and three doses of COVID-19 mRNA vaccines: a retrospective observational study from the COVID-19 and Cancer Consortium

2023· article· en· W4320519460 sur OpenAlexaff
Toni K. Choueiri, Chris Labaki, Ziad Bakouny, Chih–Yuan Hsu, Andrew Schmidt, Gilberto Lopes, Clara Hwang, Sunny Singh, Chinmay Jani, Lisa B. Weissmann, Elizabeth A. Griffiths, Susan Halabi, Ulysses Wu, Stephanie Berg, Timothy E. O’Connor, Trisha M. Wise‐Draper, Orestis A. Panagiotou, Elizabeth J. Klein, Monika Joshi, Fares Yared, Míriam Santos Dutra, Na Tosha Gatson, Sibel Blau, Harpreet Singh, Rahul Nanchal, Rana R. McKay, Taylor K. Nonato, Ryann Quinn, Samuel M. Rubinstein, Matthew Puc, Blanche H. Mavromatis, Praveen Vikas, Bryan A. Faller, Howard A. Zaren, Salvatore Del Prete, Karen Russell, Daniel Y. Reuben, Melissa Accordino, Christopher R. Friese, Sanjay Mishra, Donna R. Rivera, Yu Shyr, Dimitrios Farmakiotis, Jeremy L. Warner

Notice bibliographique

RevueThe Lancet Regional Health - Americas · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueSARS-CoV-2 and COVID-19 Research
Établissements canadiensMcGill University Health Centre
Organismes subventionnairesNational Institute on Minority Health and Health DisparitiesNational Center for Advancing Translational SciencesNational Institutes of HealthNational Cancer InstituteGeorgia Clinical and Translational Science AllianceVanderbilt Institute for Clinical and Translational ResearchVanderbilt University
Mots-clésMedicineCancerOdds ratioInternal medicineClinical endpointPopulationLogistic regressionVaccinationConfoundingImmunologyClinical trial

Résumé

récupéré en direct d'OpenAlex

Background: Breakthrough SARS-CoV-2 infections following vaccination against COVID-19 are of international concern. Patients with cancer have been observed to have worse outcomes associated with COVID-19 during the pandemic. We sought to evaluate the clinical characteristics and outcomes of patients with cancer who developed breakthrough SARS-CoV-2 infections after 2 or 3 doses of mRNA vaccines. Methods: We evaluated the clinical characteristics of patients with cancer who developed breakthrough infections using data from the multi-institutional COVID-19 and Cancer Consortium (CCC19; NCT04354701). Analysis was restricted to patients with laboratory-confirmed SARS-CoV-2 diagnosed in 2021 or 2022, to allow for a contemporary unvaccinated control population; potential differences were evaluated using a multivariable logistic regression model after inverse probability of treatment weighting to adjust for potential baseline confounding variables. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) are reported. The primary endpoint was 30-day mortality, with key secondary endpoints of hospitalization and ICU and/or mechanical ventilation (ICU/MV). Findings: The analysis included 2106 patients, of which 443 and 257 had received 2 or 3 doses of an mRNA vaccine prior to infection, respectively. Hematologic malignancies and recent receipt of systemic anti-neoplastic therapy were more frequent among vaccinated patients. Vaccination was associated with improved outcomes: in the primary analysis, 2 doses (aOR: 0.66, 95%CI: 0.49-0.97) and 3 doses (aOR: 0.32, 95%CI: 0.16-0.61) were associated with decreased 30-day mortality. There were similar findings for the key secondary endpoints of ICU/MV (aOR: 0.60, 95%CI: 0.43-0.83 and 0.37, 95%CI: 0.22-0.61) and hospitalization (aOR: 0.58, 95%CI: 0.45-0.74 and 0.30, 95%CI: 0.21-0.42) for 2 and 3 doses, respectively. Black patients had higher rates of ICU/MV and hospitalization (aOR: 1.42, 95%CI: 1.00-2.01 and 1.42, 95%CI: 1.07-1.87, respectively). Interpretation: Vaccination against COVID-19, especially with additional doses, is a fundamental strategy in the prevention of adverse outcomes including death, among patients with cancer. Trial Registration: This ongoing study is registered on ClinicalTrials.gov (NCT04354701). Funding: Declaration of Interest: TKC reports grants, personal fees and non-financial support from Merck, BMS, Exelixis, Astra Zeneca, Eli Lilly, Eisai, Novartis, GSK, Pfizer, EMD Serono; stocks in Pionyr, Tempest, outside the submitted work; In addition, TKC reports patent: pending International Patent Application No. PCT/US2018/12209, entitled “PBRM1 Biomarkers Predictive of Anti-Immune Checkpoint Response,” filed January 3, 2018, claiming priority to U.S. Provisional Patent Application No. 62/445,094, filed January 11, 2017; pending International Patent Application No.PCT/US2018/058430, entitled “Biomarkers of Clinical Response and Benefit to Immune Checkpoint Inhibitor Therapy,” filed October 31, 2018, claiming priority to U.S. Provisional Patent Application No. 62/581,175, filed November 3, 2017; TKC sits on National Comprehensive Cancer Network kidney panel; CL reports grants from Genentech/ImCore; ZB reports non-financial support from Bristol Myers Squibb, grants from Genentech/ImCore, personal fees from UpToDate, outside the submitted work; ALS reports non-financial support from Astellas and Pfizer outside the submitted work; GdLL reports personal fees from Boehringer Ingelheim, Pfizer, AstraZeneca; grants from AstraZeneca, Merck Sharp & Dohme, EMD Serono, AstraZeneca, Blueprint Medicines, Tesaro, Bavarian Nordic, Novartis, G1 Therapeutics, Adaptimmune, BMS, GSK, Abbvie, Rgenix, Pfizer, Roche, Genentech, Eli Lilly, Janssen; personal fees from Boehringer Ingelheim, Pfizer, E.R. Squibb Sons, LLC, Janssen; all outside the submitted work; CH reports grants from Merck, Bayer, Genentech, AstraZeneca, Bausch Health; Consulting fees from Tempus, Genzyme, EMD Sorono, payment or honoraria from OncLive/MJH Life Sciences, support for attending meetings and/or travel from Merck, participation on a data safety monitoring or advisory board of Henry Ford Cancer Institute, Hoosier Cancer Research Network; Leadership or fiduciary role in Wayne County Medical Society of Southeast Michigan; Stock or stock options in Johnson and Johnson, all outside the submitted work; EAG reports Consulting fees from Alexion Inc, Picnic Health, AbbVie, CTI Biopharma, Genentech Inc., Novartis, Celgene/Bristol Myers-Squibb, Takeda oncology, Taiho Oncology and Research Funding from Genentech Inc, Astex Pharmaceuticals, and BluePrint Medicines, outside the submitted work; SH reports grants/research supports from ASCO TAPUR, Astellas; honoraria or consultation fees from Sanofi, Aveo Oncology, outside the submitted work; SB reports Consulting fees from BMS, Exelexis, Eisai, Pfizer, Myovant, SeaGen; Payment or honoraria from Exelexis, Eisai, BMS; Participation on a Data Safety Monitoring Board or Advisory Board from SeaGen, Pfizer, Myovant; Stock or stock options in Natera; outside the submitted work; MJ reports grants from AstraZeneca, Pfizer; Eisai, personal fees from Seagen, Sanofi, outside the submitted work; NTNG reports personal fees from Novocure, outside the submitted work; RRM reports Advisory board/consultant – Aveo, AstraZeneca, Bayer, Bristol Myers Squib, Calithera, Caris, Dendreon, Exelixis, Janssen, Merck, Myovant, Novartis, Pfizer, Sanofi, Sorrento therapeutics, Pfizer, Tempus, Vividion, unrelated to this work; SMR reports advisory for Roche, Janssen, Sanofi, and EUSA Pharma, unrelated to this work; PV reports institutional research funding from Sanofi; stocks or stock options in Novavax, Biontech; HAZ acknowledges support from Georgia NCORP; CRF reports grants from Merck Foundation, grants from NCCN/Pfizer, grants from National Cancer Institute, other from National Cancer Institute, other from Patient-Centered Outcomes Research Institute, outside the submitted work; SM reports support from National Cancer Institute, and Intl Assoc. for the Study of Lung Cancer during the conduct of the study; and personal fees from National Geographic outside the submitted work; DF reports Grants or contracts from Merck, Viracor, Astellas; Support for attending meetings and/or travel from Viracor; outside the submitted work; JLW reports grants from NIH during the conduct of the study; personal fees from Roche, Westat, Flatiron Health, Melax Tech, IBM Watson Health, ownership of HemOnc.org LLC, grants from AACR; outside the submitted work; C-YH, SRKS, CJ, LBW, UW, TEO'C, TMW-D, OAP, EJK, HS, RN, TKN, RQ, MP, BHM, SADP, KR, BF, DYR, MKA, HS, DRR, YS, SB have nothing to disclose. Ethical Approval: This study was exempt from Institutional Review Board (IRB) review (VUMC IRB#200467) and approved by IRBs at participating sites.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,026

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,223
Tête enseignante GPT0,467
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations39
Publié2023
Routes d'admission1
Résumé présentoui

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