Real-World Risk of Severe Cytopenias in Multiple Myeloma Patients Sequentially Treated with Immunomodulatory Drugs.

INTRODUCTION: Most multiple myeloma (MM) patients experience cytopenias, likely driven by both disease and treatment-related factors. Immunomodulatory agents (IMiDs), which form the backbone of most anti-myeloma regimens, are known to cause higher grade cytopenias. In this context, the impact of sequential IMiD treatments on cytopenia risk is unknown. METHODS: We evaluated the cumulative risks of severe cytopenias following second line of therapy (LOT) initiation in 5573 MM patients in the Flatiron Health database. Patients for whom both LOTs 1 and 2 contained IMiDs were considered "sequentially exposed"; those for whom neither contained IMiDs were "never exposed." RESULTS: For the neutropenia outcome, compared to the never exposed, the sequentially exposed had the highest 1-year risk (risk difference [RD] 12%), followed by those only recently exposed during LOT 2 (RD 8%), then by those with only past exposure during LOT 1 (RD 5%). A similar pattern was observed for leukopenia, but no meaningful differences were observed for anemia or thrombocytopenia. The associations between sequential exposure, versus never, with neutropenia and leukopenia were even stronger among those with a recent cytopenia history. CONCLUSION: Results suggest that sequential exposure to IMiDs is a risk factor for higher grade cytopenias. These findings have profound clinical implications in choosing newer LOTs with potential risks of cytopenia.

Influence of Incomplete Death Information on Cumulative Risk Estimates in United States Claims Data.

Administrative claims databases often do not capture date or fact of death, so studies using these data may inappropriately treat death as a censoring event-equivalent to other withdrawal reasons-rather than a competing event. We examined 1-, 3-, and 5-year inverse-probability-of-treatment-weighted cumulative risks of a composite cardiovascular outcome among 34,527 initiators of telmisartan (exposure) and ramipril (referent) ages ≥55 in Optum claims from 2003 to 2020. Differences in cumulative risks of the cardiovascular endpoint due to censoring of death (cause-specific), as compared to treating death as a competing event (sub-distribution), increased with greater follow-up time and older age, where event and mortality risks were higher. Among ramipril users (selected results), 5-year cause-specific and sub-distribution cumulative risk estimates per 100, respectively, were 16.4 (95% CI 15.3, 17.5) and 16.2 (95% CI 15.1, 17.3) among ages 55-64 (difference=0.2) and were 43.2 (95% CI 41.3, 45.2) and 39.7 (95% CI 37.9, 41.4) among ages ≥75 (difference=3.6). Plasmode simulation results demonstrated the differences in cause-specific versus sub-distribution cumulative risks to increase with increasing mortality rate. We suggest researchers consider the cohort's baseline mortality risk when deciding whether real-world data with incomplete death information can be used without concern.

Use of Sodium-Glucose Cotransporter-2 Inhibitors and Angiotensin Receptor-Neprilysin Inhibitors in Patients With Atrial Fibrillation and Heart Failure From 2021 to 2022: An Analysis of Real-World Data.

BACKGROUND: Contemporary use of sodium-glucose cotransporter-2 inhibitors (SGLT2i) and angiotensin receptor-neprilysin inhibitors (ARNi) in patients with atrial fibrillation (AF) and heart failure (HF) has not been described. METHODS AND RESULTS: We analyzed the MarketScan databases for the period January 1, 2021 to July 30, 2022. Validated algorithms were used to identify patients with AF and HF, and to classify patients into HF with reduced ejection fraction (HFrEF) or HF with preserved ejection fraction (HFpEF). We assessed the prevalence of SGLT2i and ARNi use overall and by HF type. Additionally, we explored correlates of lower use, including demographics and comorbidities. The study population included 60 927 patients (mean age, 75 years; 43% women) diagnosed with AF and HF (85% with HFpEF, 15% with HFrEF). Prevalence of ARNi use was 11% overall (30% in HFrEF, 8% in HFpEF), whereas the corresponding figure was 6% for SGLT2i (13% in HFrEF, 5% in HFpEF). Use of both medications increased over the study period: ARNi from 9% to 12% (22%-29% in HFrEF, 6%-8% in HFpEF), and SGLT2i from 3% to 9% (6%-16% in HFrEF, 2%-7% in HFpEF). Female sex, older age, and specific comorbidities were associated with lower use of these 2 medication types overall and by HF type. CONCLUSIONS: Use of ARNi and SGLT2i in patients with AF and HF is suboptimal, particularly among women and older individuals, though use is increasing. These results underscore the need for understanding reasons for these disparities and developing interventions to improve adoption of evidence-based therapies among patients with comorbid AF and HF.

Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother-Infant Linkage in the Japan Medical Data Center Claims Database.

Purpose: Observational postapproval safety studies are needed to inform medication safety during pregnancy. Real-world databases can be valuable for supporting such research, but fitness for regulatory purpose must first be vetted. Here, we demonstrate a fit-for-purpose assessment of the Japan Medical Data Center (JMDC) claims database for pregnancy safety regulatory decision-making. Patients and Methods: The Duke-Margolis framework considers a database's fitness for regulatory purpose based on relevancy (capacity to answer the research question based on variable availability and a sufficiently sized, representative population) and quality (ability to validly answer the research question based on data completeness and accuracy). To assess these considerations, we examined descriptive characteristics of infants and pregnancies among females ages 12-55 years in the JMDC between January 2005 and March 2022. Results: For relevancy, we determined that critical data fields (maternal medications, infant major congenital malformations, covariates) are available. Family identification codes permitted linkage of 385,295 total mother-infant pairs, 57% of which were continuously enrolled during pregnancy. The prevalence of specific congenital malformation subcategories and maternal medical conditions were representative of the general population, but preterm births were below expectations (3.6% versus 5.6%) in this population. For quality, our methods are expected to accurately identify the complete set of mothers and infants with a shared health insurance plan. However, validity of gestational age information was limited given the high proportion (60%) of missing live birth delivery codes coupled with suppression of infant birth dates and inaccessibility of disease codes with gestational week information. Conclusion: The JMDC may be well suited for descriptive studies of pregnant people in Japan (eg, comorbidities, medication usage). More work is needed to identify a method to assign pregnancy onset and delivery dates so that in utero medication exposure windows can be defined more precisely as needed for many regulatory postapproval pregnancy safety studies.

Periconceptional Dietary Patterns and Adverse Pregnancy and Birth Outcomes.

BACKGROUND: The periconceptional period is a critical window for the origins of adverse pregnancy and birth outcomes, yet little is known about the dietary patterns that promote perinatal health. OBJECTIVE: We used machine learning methods to determine the effect of periconceptional dietary patterns on risk of preeclampsia, gestational diabetes, preterm birth, small-for-gestational-age (SGA) birth, and a composite of these outcomes. METHODS: We used data from 8259 participants in the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (8 US medical centers, 2010‒2013). Usual daily periconceptional intake of 82 food groups was estimated from a food frequency questionnaire. We used k-means clustering with a Euclidean distance metric to identify dietary patterns. We estimated the effect of dietary patterns on each perinatal outcome using targeted maximum likelihood estimation and an ensemble of machine learning algorithms, adjusting for confounders including health behaviors and psychological, neighborhood, and sociodemographic factors. RESULTS: The 4 dietary patterns that emerged from our data were identified as "Sandwiches and snacks" (34% of the sample); "High fat, sugar, and sodium" (29%); "Beverages, refined grains, and mixed dishes" (21%); and "High fruits, vegetables, whole grains, and plant proteins" (16%). One-quarter of pregnancies had preeclampsia (8% incidence), gestational diabetes (5%), preterm birth (8%), or SGA birth (8%). Compared with the "High fat, sugar, and sodium" pattern, there were 3.3 to 4.3 fewer cases of the composite adverse outcome per 100 pregnancies among participants following the "Beverages, refined grains and mixed dishes" pattern (risk difference -0.043; 95% confidence interval -0.078, -0.009), "High fruits, vegetables, whole grains and plant proteins" pattern (-0.041; 95% confidence interval -0.078, -0.004), and "Sandwiches and snacks" pattern (-0.033; 95% confidence interval -0.065, -0.002). CONCLUSIONS: Our results highlight that there are a variety of periconceptional dietary patterns that are associated with perinatal health and reinforce the negative health implications of diets high in fat, sugars, and sodium.

Use of SGLT2i and ARNi in patients with atrial fibrillation and heart failure in 2021-2022: an analysis of real-world data.

Objective: To evaluate utilization of sodium-glucose cotransporter-2 inhibitors (SGLT2i) and angiotensin receptor neprilysin inhibitors (ARNi) in patients with atrial fibrillation (AF) and heart failure (HF). Methods: We analyzed the MarketScan databases for the period 1/1/2021 to 6/30/2022. Validated algorithms were used to identify patients with AF and HF, and to classify patients into HF with reduced ejection fraction (HFrEF) or preserved ejection fraction (HFpEF). We assessed the prevalence of SGLT2i and ARNi use overall and by HF type. Additionally, we explored correlates of lower utilization, including demographics and comorbidities. Results: The study population included 60,927 patients (mean age 75, 43% female) diagnosed with AF and HF (85% with HFpEF, 15% with HFrEF). Prevalence of ARNi use was 11% overall (30% in HFrEF, 8% in HFpEF), while the corresponding figure was 6% for SGLT2i (13% in HFrEF, 5% in HFpEF). Use of both medications increased over the study period: ARNi from 9% to 12% (from 22% to 29% in HFrEF, from 6% to 8% in HFpEF), and SGLT2i from 3% to 9% (from 6% to 16% in HFrEF, from 2% to 7% in HFpEF). Female sex, older age, and specific comorbidities were associated with lower utilization of these two medication types overall and by HF type. Conclusion: Use of ARNi and SGLT2i in patients with AF and HF is suboptimal, particularly among females and older individuals, though utilization is increasing. These results underscore the need for understanding reasons for these disparities and developing interventions to improve adoption of evidence-based therapies among patients with comorbid AF and HF.

Is the Association Between Fruits and Vegetables and Preeclampsia Due to Higher Dietary Vitamin C and Carotenoid Intakes?

BACKGROUND: Diets dense in fruits and vegetables are associated with a reduced risk of preeclampsia, but pathways underlying this relationship are unclear. Dietary antioxidants may contribute to the protective effect. OBJECTIVE: We determined the extent to which the effect of dietary fruit and vegetable density on preeclampsia is because of high intakes of dietary vitamin C and carotenoids. METHODS: We used data from 7572 participants in the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (8 United States medical centers, 2010‒2013). Usual daily periconceptional intake of total fruits and total vegetables was estimated from a food frequency questionnaire. We estimated the indirect effect of ≥2.5 cups/1000 kcal of fruits and vegetables through vitamin C and carotenoid on the risk of preeclampsia. We estimated these effects using targeted maximum likelihood estimation and an ensemble of machine learning algorithms, adjusting for confounders, including other dietary components, health behaviors, and psychological, neighborhood, and sociodemographic factors. RESULTS: Participants who consumed ≥2.5 cups of fruits and vegetables per 1000 kcal were less likely than those who consumed <2.5 cups/1000 kcal to develop preeclampsia (6.4% compared with 8.6%). After confounder adjustment, we observed that higher fruit and vegetable density was associated with 2 fewer cases of preeclampsia (risk difference: -2.0; 95% CI: -3.9, -0.1)/100 pregnancies compared with lower density diets. High dietary vitamin C and carotenoid intake was not associated with preeclampsia. The protective effect of high fruit and vegetable density on the risk of preeclampsia and late-onset preeclampsia was not mediated through dietary vitamin C and carotenoids. CONCLUSIONS: Evaluating other nutrients and bioactives in fruits and vegetables and their synergy is worthwhile, along with characterizing the effect of individual fruits or vegetables on preeclampsia risk.

Experiences of Racial Discrimination and Periconceptional Diet Quality.

BACKGROUND: Racism is a key determinant of perinatal health disparities. Poor diet may contribute to this effect, but research on racism and dietary patterns is limited. OBJECTIVE: We aimed to describe the relation between experiences of racial discrimination and adherence to the 2015‒2020 Dietary Guidelines for Americans. METHODS: We used data from a prospective pregnancy cohort study conducted at 8 United States medical centers (2010‒2013). At 6‒13 weeks of gestation, 10,038 nulliparous people with singleton pregnancies were enrolled. Participants completed a Block food frequency questionnaire, assessing usual diet in the 3 mo around conception, and the Krieger Experiences of Discrimination Scale, assessing the number of situational domains (e.g., at school and on the street) in which participants ever experienced racial discrimination. Alignment of dietary intake with the 2015-2020 Dietary Guidelines for Americans was assessed using the Healthy Eating Index (HEI)-2015. RESULTS: The study showed that 49%, 44%, 35%, and 17% of the Asian, Black, Hispanic, and White participants reported experiences of racial discrimination in any domain. Most participants experienced discrimination in 1 or 2 situational domains. There were no meaningful differences in HEI-2015 total or component scores in any racial or ethnic group according to count of self-reported domains in which individuals experienced discrimination. For example, mean total scores were 57‒59 among Black, 61‒66 among White, 61‒63 among Hispanic, and 66‒69 among Asian participants across the count of racial discrimination domains. CONCLUSIONS: This null association stresses the importance of going beyond interpersonal racial discrimination to consider the institutions, systems, and practices affecting racialized people to eliminate persistent inequalities in diet and perinatal health.

Longitudinal profiles of neighborhood socioeconomic vulnerability influence blood pressure changes across the female midlife period.

PURPOSE: To examine whether longitudinal exposure to neighborhood socioeconomic vulnerability influences blood pressure changes throughout midlife in a racially, ethnically, and geographically-diverse cohort of women transitioning through menopause. METHODS: We used longitudinal data on 2738 women (age 42-52 at baseline) living in six United States cities from The Study of Women's Health Across the Nation. Residential histories, systolic blood pressures (SBP), and diastolic blood pressures (DBP) were collected annually for ten years. We used longitudinal latent profile analysis to identify patterns of neighborhood socioeconomic vulnerability occurring from 1996 to 2007 in participant neighborhoods. We used linear mixed-effect models to determine if a woman's neighborhood profile throughout midlife was associated with blood pressure changes. RESULTS: We identified four unique profiles of neighborhood socioeconomic vulnerability - differentiated by residential socioeconomic status, population density, and vacant housing conditions - which remained stable across time. Women residing in the most socioeconomically vulnerable neighborhoods experienced the steepest increase in annual SBP growth by 0.93 mmHg/year (95% CI: 0.65-1.21) across ten-year follow-up. CONCLUSIONS: Neighborhood socioeconomic vulnerability was significantly associated with accelerated SBP increases throughout midlife among women.

Does heterogeneity underlie differences in treatment effects estimated from SuperLearner versus logistic regression? An application in nutritional epidemiology.

PURPOSE: A strength of SuperLearner is that it may accommodate key interactions between model variables without a priori specification. In prior research, protective associations between fruit intake and preeclampsia were stronger when estimated using SuperLearner with targeted maximum likelihood estimation (TMLE) compared with multivariable logistic regression without any interaction terms. We explored whether heterogeneity (i.e., differences in the effect estimate due to interactions between fruit intake and covariates) may partly explain differences in estimates from these two models. METHODS: Using a U.S. prospective pregnancy cohort (2010-2013, n = 7781), we estimated preeclampsia risk differences (RDs) for higher versus lower fruit density using multivariable logistic regression and included two-way statistical interactions between fruit density and each of the 25 model covariates. We compared the RDs with those from SuperLearner with TMLE (gold standard) and logistic regression with no interaction. RESULTS: From the logistic regression models with two-way statistical interactions, 48% of the preeclampsia RDs were ≤-0.02 (closer to SuperLearner with TMLE estimate); 40% equaled -0.01 (same as logistic regression with no interaction estimate); the minority of RDs were at or crossed the null. CONCLUSIONS: Our exploratory analysis provided preliminary evidence that heterogeneity may partly explain differences in estimates from logistic regression versus SuperLearner with TMLE.

Racial Differences in Fatal Out-of-Hospital Coronary Heart Disease and the Role of Income in the Atherosclerosis Risk in Communities Cohort Study (1987 to 2017).

Black patients have higher incident fatal coronary heart disease (CHD) rates than do their White counterparts. Racial differences in out-of-hospital fatal CHD could explain the excess risk in fatal CHD among Black patients. We examined racial disparities in in- and out-of-hospital fatal CHD among participants with no history of CHD, and whether socioeconomic status might play a role in this association. We used data from the ARIC (Atherosclerosis Risk in Communities) study, including 4,095 Black and 10,884 White participants, followed between 1987 and 1989 until 2017. Race was self-reported. We examined racial differences in in- and out-of-hospital fatal CHD with hierarchical proportional hazard models. We then examined the role of income in these associations, using Cox marginal structural models for a mediation analysis. The incidence of out-of-hospital and in-hospital fatal CHD was 1.3 and 2.2 in Black participants, and 1.0 and 1.1 in White participants, respectively, per 1,000 person-years. The gender- and age-adjusted hazard ratios comparing out-of-hospital and in-hospital incident fatal CHD in Black with that in White participants were 1.65 (1.32 to 2.07) and 2.37 (1.96 to 2.86), respectively. The income-controlled direct effects of race in Black versus White participants decreased to 1.33 (1.01 to 1.74) for fatal out-of-hospital and to 2.03 (1.61 to 2.55) for fatal in-hospital CHD in Cox marginal structural models. In conclusion, higher rates of fatal in-hospital CHD in Black participants than in their White counterparts likely drive the overall racial differences in fatal CHD. Income largely explained racial differences in both fatal out-of-hospital CHD and fatal in-hospital CHD.

Estimation of the Time-Varying Incremental Effect of Low-dose Aspirin on Incidence of Pregnancy.

BACKGROUND: In many research settings, the intervention implied by the average causal effect of a time-varying exposure is impractical or unrealistic, and we might instead prefer a more realistic target estimand. Instead of requiring all individuals to be always exposed versus unexposed, incremental effects quantify the impact of merely shifting each individual's probability of being exposed. METHODS: We demonstrate the estimation of incremental effects in the time-varying setting, using data from the Effects of Aspirin in Gestation and Reproduction trial, which assessed the effect of preconception low-dose aspirin on pregnancy outcomes. Compliance to aspirin or placebo was summarized weekly and was affected by time-varying confounders such as bleeding or nausea. We sought to estimate what the incidence of pregnancy by 26 weeks postrandomization would have been if we shifted each participant's probability of taking aspirin or placebo each week by odds ratios (OR) between 0.30 and 3.00. RESULTS: Under no intervention (OR = 1), the incidence of pregnancy was 77% (95% CI: 74%, 80%). Decreasing women's probability of complying with aspirin had little estimated effect on pregnancy incidence. When we increased women's probability of taking aspirin, estimated incidence of pregnancy increased, from 83% (95% confidence interval [CI] = 79%, 87%) for OR = 2 to 89% (95% CI = 84%, 93%) for OR=3. We observed similar results when we shifted women's probability of complying with a placebo. CONCLUSIONS: These results estimated that realistic interventions to increase women's probability of taking aspirin would have yielded little to no impact on the incidence of pregnancy, relative to similar interventions on placebo.

A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and G-Computation in Survival Analysis.

Inverse probability weighting (IPW) and g-computation are commonly used in time-varying analyses. To inform decisions on which to use, we compared these methods using a plasmode simulation based on data from the Effects of Aspirin in Gestation and Reproduction (EAGeR) Trial (June 15, 2007-July 15, 2011). In our main analysis, we simulated a cohort study of 1,226 individuals followed for up to 10 weeks. The exposure was weekly exercise, and the outcome was time to pregnancy. We controlled for 6 confounding factors: 4 baseline confounders (race, ever smoking, age, and body mass index) and 2 time-varying confounders (compliance with assigned treatment and nausea). We sought to estimate the average causal risk difference by 10 weeks, using IPW and g-computation implemented using a Monte Carlo estimator and iterated conditional expectations (ICE). Across 500 simulations, we compared the bias, empirical standard error (ESE), average standard error, standard error ratio, and 95% confidence interval coverage of each approach. IPW (bias = 0.02; ESE = 0.04; coverage = 92.6%) and Monte Carlo g-computation (bias = -0.01; ESE = 0.03; coverage = 94.2%) performed similarly. ICE g-computation was the least biased but least precise estimator (bias = 0.01; ESE = 0.06; coverage = 93.4%). When choosing an estimator, one should consider factors like the research question, the prevalences of the exposure and outcome, and the number of time points being analyzed.

Sexually transmitted infections and risk of hypertensive disorders of pregnancy.

Hypertensive disorders of pregnancy (HDP) result in maternal morbidity and mortality but are rarely examined in perinatal studies of sexually transmitted infections. We examined associations between common sexually transmitted infections and HDP among 38,026 singleton pregnancies. Log-binomial regression calculated relative risk (RRs) and 95% confidence intervals (CIs) for associations with gestational hypertension, preeclampsia with severe features, mild preeclampsia, and superimposed preeclampsia. All models were adjusted for insurance type, maternal age, race/ethnicity, and education. Additional adjustments resulted in similar effect estimates. Chlamydia was associated with preeclampsia with severe features (RRadj. 1.4, 95% CI 1.1, 1.9). Effect estimates differed when we examined first prenatal visit diagnosis only (RRadj. 1.3, 95% CI 0.9, 1.9) and persistent or recurrent infection (RRadj. 2.0, 95% CI 1.1, 3.4). For chlamydia (RRadj. 2.0, 95% CI 1.3, 2.9) and gonorrhea (RRadj. 3.0, 95% CI 1.1, 12.2), women without a documented treatment were more likely to have preeclampsia with severe features. Among a diverse perinatal population, sexually transmitted infections may be associated with preeclampsia with severe features. With the striking increasing rates of sexually transmitted infections, there is a need to revisit the burden in pregnant women and determine if there is a link between infections and hypertensive disorders of pregnancy.