When Should I Get My Next COVID-19 Vaccine? Data From the Surveillance of Responses to COVID-19 Vaccines in Systemic Immune-Mediated Inflammatory Diseases (SUCCEED) Study.

OBJECTIVE: To determine how serologic responses to coronavirus disease 2019 (COVID-19) vaccination and infection in immune-mediated inflammatory disease (IMID) are affected by time since last vaccination and other factors. METHODS: Post-COVID-19 vaccination, data, and dried blood spots or sera were collected from adults with rheumatoid arthritis, inflammatory bowel disease, systemic lupus erythematosus, ankylosing spondylitis and spondylarthritis, and psoriasis and psoriatic arthritis. The first sample was collected at enrollment, then at 2 to 4 weeks and 3, 6, and 12 months after the latest vaccine dose. Multivariate generalized estimating equation regressions (including medications, demographics, and vaccination history) evaluated serologic response, based on log-transformed anti-receptor-binding domain (RBD) IgG titers; we also measured antinucleocapsid (anti-N) IgG. RESULTS: Positive associations for log-transformed anti-RBD titers were seen with female sex, number of doses, and self-reported COVID-19 infections in 2021 to 2023. Negative associations were seen with prednisone, anti-tumor necrosis factor agents, and rituximab. Over the 2021-2023 period, most (94%) of anti-N positivity was associated with a self-reported infection in the 3 months prior to testing. From March 2021 to February 2022, anti-N positivity was present in 5% to 15% of samples and was highest in the post-Omicron era, with antinucleocapsid positivity trending to 30% to 35% or higher as of March 2023. Anti-N positivity in IMID remained lower than Canada's general population seroprevalence (> 50% in 2022 and > 75% in 2023). Time since last vaccination was negatively associated with log-transformed anti-RBD titers, particularly after 210 days. CONCLUSION: Ours is the first pan-Canadian IMID assessment of how vaccine history and other factors affect serologic COVID-19 vaccine responses. These findings may help individuals personalize vaccination decisions, including consideration of additional vaccination when > 6 months has elapsed since last COVID-19 vaccination/infection.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017. OBJECTIVES: To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach. SEARCH METHODS: We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022. SELECTION CRITERIA: We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention. DATA COLLECTION AND ANALYSIS: Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence. MAIN RESULTS: This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015. AUTHORS' CONCLUSIONS: Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.