Vaccination Guidelines for Patients With Immune-Mediated Disorders on Immunosuppressive Therapies
Bibliographic record
Abstract
BACKGROUND:: Patients with immune-mediated diseases on immunosuppressive therapies have more infectious episodes than healthy individuals, yet vaccination practices by physicians for this patient population remain suboptimal. OBJECTIVES:: To evaluate the safety and efficacy of vaccines in individuals exposed to immunosuppressive therapies and provide evidence-based clinical practice recommendations. METHODS:: A literature search for vaccination safety and efficacy in patients on immunosuppressive therapies (2009-2017) was conducted. Results were assessed using the Grading of Recommendation, Assessment, Development, and Evaluation system. RESULTS:: Several immunosuppressive therapies attenuate vaccine response. Thus, vaccines should be administered before treatment whenever feasible. Inactivated vaccines can be administered without treatment discontinuation. Similarly, evidence suggests that the live zoster vaccine is safe and effective while on select immunosuppressive therapy, although use of the subunit vaccine is preferred. Caution regarding other live vaccines is warranted. Drug pharmacokinetics, duration of vaccine-induced viremia, and immune response kinetics should be considered to determine appropriate timing of vaccination and treatment (re)initiation. Infants exposed to immunosuppressive therapies through breastmilk can usually be immunized according to local guidelines. Intrauterine exposure to immunosuppressive agents is not a contraindication for inactivated vaccines. Live attenuated vaccines scheduled for infants and children ⩾12 months of age, including measles, mumps, rubella, and varicella, can be safely administered as sufficient time has elapsed for drug clearance. CONCLUSIONS:: Immunosuppressive agents may attenuate vaccine responses, but protective benefit is generally maintained. While these recommendations are evidence based, they do not replace clinical judgment, and decisions regarding vaccination must carefully assess the risks, benefits, and circumstances of individual 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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".