Faculty Bibliography

BACKGROUND:Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations. METHODS:Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital. RESULTS:Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model's prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/. CONCLUSIONS:Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers' practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.

Recently, the misuse of race as a biological variable, rather than a social construct, in biomedical research has received national attention for its contributions to medical bias. In national transplant registry data, bias may arise from measurement imprecision because of the collection of provider-perceived race rather than patients' own self-report.

Heterologous vaccination ("mixing platforms") for the third (D3) dose of SARS-CoV-2 vaccine is a potential strategy to improve antibody responses in solid organ transplant recipients (SOTRs), but data are mixed regarding potential differential immunogenicity. We assessed for differences in immunogenicity and tolerability of homologous (BNT162b2 or mRNA-1273; D3-mRNA) versus heterologous (Ad.26.COV2.S; D3-JJ) D3 among 377 SARS-CoV-2-infection naïve SOTRs who remained seronegative after two mRNA vaccines. We measured anti-spike titers and used weighted Poisson regression to evaluate seroconversion and development of high-titers, comparing D3-JJ to D3-mRNA, at 1-, 3-, and 6 month post-D3. 1-month post-D3, seroconversion (63% vs. 52%, p = .3) and development of high-titers (29% vs. 25%, p = .7) were comparable between D3-JJ and D3-mRNA recipients. 3 month post-D3, D3-JJ recipients were 1.4-fold more likely to seroconvert (80% vs. 57%, weighted incidence-rate-ratio: wIRR = _1.10 1.40_1.77 , p = .006) but not more likely to develop high-titers (27% vs. 22%, wIRR = _0.44 0.92_1.93 , p = .8). 6 month post-D3, D3-JJ recipients were 1.41-fold more likely to seroconvert (88% vs. 59%, wIRR = _1.04 1.41_1.93 , p = .029) and 2.63-fold more likely to develop high-titers (59% vs. 21%, wIRR = _1.38 2.63_5.00 , p = .003). There was no differential signal in alloimmune events or reactogenicity between platforms. SOTRs without antibody response after two mRNA vaccines may derive benefit from heterologous Ad.26.COV2.S D3.

BACKGROUND:Medicaid expansion has led to earlier stage diagnoses in several cancers but has not been studied in hepatocellular carcinoma (HCC), a disease with complex risk factors. We examined the effect of Medicaid expansion on the diagnosis of HCC and associations with county-level social vulnerability. METHODS:Patients with HCC <65 years of age were identified from the SEER database (2010-2016). County-level social vulnerability factors were obtained from the CDC SVI and BRFSS. A Difference-in-Difference analysis evaluated change in early-stage diagnoses (stage I-II) between expansion and non-expansion states. A Difference-in-Difference-in-Difference analysis evaluated expansion impact among counties with higher proportions of social vulnerability. RESULTS:Of 19,751 patients identified, 81.5% were in expansion states. Uninsured status decreased in expansion states (6.3%-2.4%, p < 0.0001) and remained unchanged in non-expansion states (12.7%-14.8%, p = 0.43). There was no significant difference in the incidence of early-stage diagnoses between expansion states and non-expansion states. Results were consistent when accounting for social vulnerability. CONCLUSION/CONCLUSIONS:Medicaid expansion was not associated with earlier stage diagnoses in patients with HCC, including those with higher social vulnerability. Unlike other cancers, expanded access did not translate into higher utilization of care in HCC, suggesting barriers on a multitude of levels.