Quantitative Analysis of SARS-CoV-2 Antibody Levels in Cancer Patients Post Three Doses of Immunization and Prior to Breakthrough COVID-19 Infections
Bibliographic record
Abstract
(1) Background: COVID-19 vaccine effectiveness should be carefully evaluated and explicitly defined. To our knowledge, this is the first report to quantitatively evaluate humoral responses post 3 doses of SARS-CoV-2 immunization and prior to breakthrough COVID-19 infection in Canadian cancer patients. (2) Methods: In a prospective cohort study, we enrolled 185 cancer participants post COVID-19 vaccination in Kingston, Ontario, Canada. IgG antibodies against the SARS-CoV-2 spike receptor–binding domain were quantified by immunoassay post three doses of immunization. With the COVID-19 rapid antigen test and polymerase chain reaction (PCR), 16 breakthrough infections were identified. Results: Following SARS-CoV-2 vaccination (including BNT162b2, AZD1222, and mRNA-1273), the mean serum anti-spike protein antibody level was 197.2 BAU/mL (binding antibody unit, SD ± 393.9), 1335.9 BAU/mL (±3337.8), and 3164.8 BAU/mL (±6500.9) post the first, second, and third dose of vaccination. Observed differences were significant (p ≤ 0.001). The average antibody level of 3164.8 BAU/mL post the third dose was 89.9 times that of the seroconversion level (35.2 BAU/mL). This indicates that most vaccines approved are effective in producing robust antibody responses. In 11 breakthrough cases confirmed by PCR, prior to infection, the average antibody concentration was 3675.6 BAU/mL with the highest concentration being 9107.4 BAU/mL. Compared with this average antibody concentration of 3675.6 BAU/mL (104.4 times that of the seroconversion concentration), 0% of single dosed, 9.6% of double vaccinated, and 29.5% of triple vaccinated cancer patients had higher SARS-CoV-2 antibody levels. When patients were split into hematological and solid cancer, the hematological cancer group demonstrated lower serological responses than the solid cancer group in the first and second doses (first dose, average concentration 11.1 vs. 201.4 BAU/mL, respectively, p < 0.05; second dose, average concentration 441.5 vs. 1725.9 BAU/mL, respectively, p < 0.05). There was no difference in the third dose level (1756.3 vs. 2548.0 BAU/mL, p = 0.21). (4) Conclusions: Most vaccines were effective in producing robust antibody responses when more than one dose was given, and the more doses the higher the serological response. Likely due to the highly contagious nature of SARS-CoV-2 variants, a significant number of participants had SARS-CoV-2 antibody responses lower than the average antibody concentration prior to the known breakthrough infections. Additional vaccination is likely required to ensure immunity against infection by SARS-CoV-2.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".