Patients' perspectives and safety of COVID-19 vaccination among cancer patients: A prospective single-center study.
Bibliographic record
Abstract
e24043 Background: Concerns about safety and treatment interference are known barriers to COVID-19 vaccination in cancer patients. Data on safety and tolerability in this population remain scarce. One of the objectives of this study is to describe COVID-19 vaccination safety in cancer patients. Methods: Patients diagnosed with a malignancy requiring systemic treatment in the last 12 months and undergoing COVID-19 vaccination were prospectively enrolled in this single-center study. Validated questionnaires to assess vaccine-related adverse events (VRAEs) were collected; chart review identified baseline characteristics and treatments received. Descriptive statistics and logistic regressions were performed. Results: 253 questionnaires were collected from 171 patients, enrolled between May and September 2021. 130 patients were survey-eligible after the 1st dose (D1) and 185 after 2nd dose (D2). 91 questionnaires were collected after D1 (Questionnaire 1: Q1) and 162 after D2 (Questionnaire 2: Q2). Surveys couldn’t be collected due to interval > 1 month between D1 / enrollment, patients’ unavailability, withdrawal of study or death. Median age was 55 (24-87) and 62.8% were female. 58.5% had solid tumors, treated with chemotherapy (49%) or checkpoint inhibitors only (9.5%); 19.4% malignancies were treated with targeted therapies and 22.1% had hematological malignancies. Most frequent solid tumors were breast (31.3%), lung (15.9%) and gastro-intestinal (GI) (14.3%). Patients received 45.6% Pfizer/BioNTech, 52.8% Moderna and 1.6% Oxford/AstraZeneca. A combination of 2 different vaccines was administered to 11.9%. Interval between D1 and D2 was ≤30 days in 53.1%, 31-90 days in 42.6%, and 91-180 days in 4.3%. Among all patients, 84.1% developed VRAEs after a median of 2 days post-vaccine for a median of 4 days. 74.5% had local symptoms (Sx) (pain, sensitivity and/or redness at injection site and/or arm) and 65.8% had systemic Sx. Most frequent systemic Sx were fatigue, chills or myalgia (39.4%), GI (6.3%) and fever (2.9%). Most patients (90.7%) described their Sx as having no / minimal impact (Gr 1), 7.8% reported seeking medical consultation (Gr 2), and 1.5% lead to hospitalization (Gr 3) (1 cardiovascular event, 1 infection; causality with concurrent systemic treatment not excluded and 1 due to malignancy). Gr 2, but not Gr 3, VRAEs were more common after D2 (11.4% vs 2.5%, p = 0.03). 41.7% considered their Sx as a new health problem. On multivariate analysis, younger age and female sex were significantly associated with the development of any Sx (OR 1.08, p = 0.01; OR 2.92, p = 0.02, respectively) and local Sx (OR 1.04, p = 0.04; OR 2.19, p = 0.04), but not systemic Sx or new health problem. Conclusions: Patients experienced mostly minor and transient symptoms post-vaccination; few perceived these as a new health problem. COVID-19 vaccination is overall safe and well-tolerated among cancer patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".