Mediation analysis of gestational age, congenital heart defects, and infant birth-weight

Background In this study we assessed the mediation role of the gestational age on the effect of the infant’s congenital heart defects (CHD) on birth-weight. Methods We used secondary data from the Baltimore-Washington Infant Study (1981–1989). Mediation analysis was employed to investigate whether gestational age acted as a mediator of the association between CHD and reduced birth-weight. We estimated the mediated effect, the mediation proportion, and their corresponding 95% confidence intervals (CI) using several methods. Results There were 3362 CHD cases and 3564 controls in the dataset with mean birth-weight of 3071 (SD = 729) and 3353 (SD = 603) grams, respectively; the mean gestational age was 38.9 (SD = 2.7) and 39.6 (SD = 2.2) weeks, respectively. After adjusting for covariates, the estimated mediated effect by gestational age was 113.5 grams (95% CI, 92.4–134.2) and the mediation proportion was 40.7% (95% CI, 34.7%–46.6%), using the bootstrap approach. Conclusions Gestational age may account for about 41% of the overall effect of heart defects on reduced infant birth-weight. Improved prenatal care and other public health efforts that promote full term delivery, particularly targeting high-risk families and mothers known to be carrying a fetus with CHD, may therefore be expected to improve the birth-weight of these infants and their long term health

Maximum Agreement Linear Prediction via the Concordance Correlation Coefficient

This paper examines distributional properties and predictive performance of the estimated maximum agreement linear predictor (MALP) introduced in Bottai, Kim, Lieberman, Luta, and Pena (2022) paper in The American Statistician, which is the linear predictor maximizing Lin's concordance correlation coefficient (CCC) between the predictor and the predictand. It is compared and contrasted, theoretically and through computer experiments, with the estimated least-squares linear predictor (LSLP). Finite-sample and asymptotic properties are obtained, and confidence intervals are also presented. The predictors are illustrated using two real data sets: an eye data set and a bodyfat data set. The results indicate that the estimated MALP is a viable alternative to the estimated LSLP if one desires a predictor whose predicted values possess higher agreement with the predictand values, as measured by the CCC

Mediation analysis of gestational age, congenital heart defects, and infant birth-weight

Abstract Background In this study we assessed the mediation role of the gestational age on the effect of the infant’s congenital heart defects (CHD) on birth-weight. Methods We used secondary data from the Baltimore-Washington Infant Study (1981–1989). Mediation analysis was employed to investigate whether gestational age acted as a mediator of the association between CHD and reduced birth-weight. We estimated the mediated effect, the mediation proportion, and their corresponding 95% confidence intervals (CI) using several methods. Results There were 3362 CHD cases and 3564 controls in the dataset with mean birth-weight of 3071 (SD = 729) and 3353 (SD = 603) grams, respectively; the mean gestational age was 38.9 (SD = 2.7) and 39.6 (SD = 2.2) weeks, respectively. After adjusting for covariates, the estimated mediated effect by gestational age was 113.5 grams (95% CI, 92.4–134.2) and the mediation proportion was 40.7% (95% CI, 34.7%–46.6%), using the bootstrap approach. Conclusions Gestational age may account for about 41% of the overall effect of heart defects on reduced infant birth-weight. Improved prenatal care and other public health efforts that promote full term delivery, particularly targeting high-risk families and mothers known to be carrying a fetus with CHD, may therefore be expected to improve the birth-weight of these infants and their long term health

Control of confounding in the analysis phase – an overview for clinicians

In observational studies, control of confounding can be done in the design and analysis phases. Using examples from large health care database studies, this article provides the clinicians with an overview of standard methods in the analysis phase, such as stratification, standardization, multivariable regression analysis and propensity score (PS) methods, together with the more advanced high-dimensional propensity score (HD-PS) method. We describe the progression from simple stratification confined to the inclusion of a few potential confounders to complex modeling procedures such as the HD-PS approach by which hundreds of potential confounders are extracted from large health care databases. Stratification and standardization assist in the understanding of the data at a detailed level, while accounting for potential confounders. Incorporating several potential confounders in the analysis typically implies the choice between multivariable analysis and PS methods. Although PS methods have gained remarkable popularity in recent years, there is an ongoing discussion on the advantages and disadvantages of PS methods as compared to those of multivariable analysis. Furthermore, the HD-PS method, despite its generous inclusion of potential confounders, is also associated with potential pitfalls. All methods are dependent on the assumption of no unknown, unmeasured and residual confounding and suffer from the difficulty of identifying true confounders. Even in large health care databases, insufficient or poor data may contribute to these challenges. The trend in data collection is to compile more fine-grained data on lifestyle and severity of diseases, based on self-reporting and modern technologies. This will surely improve our ability to incorporate relevant confounders or their proxies. However, despite a remarkable development of methods that account for confounding and new data opportunities, confounding will remain a serious issue. Considering the advantages and disadvantages of different methods, we emphasize the importance of the clinical input and of the interplay between clinicians and analysts to ensure a proper analysis

Risk of serious adverse effects of biological and targeted drugs in patients with rheumatoid arthritis: a systematic review meta-analysis

OBJECTIVES: To determine possible differences in serious adverse effects among the 10 currently approved biological and targeted synthetic DMARDs (b/ts-DMARDs) for RA.METHODS: Systematic review in bibliographic databases, trial registries and websites of regulatory agencies identified randomized trials of approved b/ts-DMARDs for RA. Network meta-analyses using mixed-effects Poisson regression models were conducted to calculate rate ratios for serious adverse events (SAEs) and deaths between each of the 10 drugs and control (i.e. no b/ts-DMARD treatment), based on subjects experiencing an event in relation to person-years. Confidence in the estimates was assessed by applying the Grading of Recommendations Assessment, Development and Evaluation approach (GRADE).RESULTS: A total of 117 trials (47 615 patients) were included. SAEs were more common with certolizumab compared with abatacept (rate ratio = 1.58, 95% CI: 1.18, 2.14), adalimumab (1.36, 95% CI: 1.02, 1.81), etanercept (1.60, 95% CI: 1.18, 2.17), golimumab (1.45, 95% CI: 1.00, 2.08), rituximab (1.63, 95% CI: 1.16, 2.30), tofacitinib (1.44, 95% CI: 1.03, 2.02) and control (1.45, 95% CI: 1.13, 1.87); and tocilizumab compared with abatacept (1.30, 95% CI: 1.03, 1.65), etanercept (1.31, 95% CI: 1.04, 1.67) and rituximab (1.34, 95% CI: 1.01, 1.78). No other comparisons were statistically significant. Accounting for study duration confirmed our findings for up to 6 months' treatment but not for longer-term treatment (6-24 months). No differences in mortality between b/ts-DMARDs and control were found. Based on the GRADE approach, confidence in the estimates was low due to lack of head-to-head comparison trials and imprecision in indirect estimates.CONCLUSION: Despite low confidence in the estimates, our analysis found potential differences in rates of SAEs. Our data suggest caution should be taken when deciding among available drugs. OBJECTIVES: To determine possible differences in serious adverse effects among the 10 currently approved biological and targeted synthetic DMARDs (b/ts-DMARDs) for RA.METHODS: Systematic review in bibliographic databases, trial registries and websites of regulatory agencies identified randomized trials of approved b/ts-DMARDs for RA. Network meta-analyses using mixed-effects Poisson regression models were conducted to calculate rate ratios for serious adverse events (SAEs) and deaths between each of the 10 drugs and control (i.e. no b/ts-DMARD treatment), based on subjects experiencing an event in relation to person-years. Confidence in the estimates was assessed by applying the Grading of Recommendations Assessment, Development and Evaluation approach (GRADE).RESULTS: A total of 117 trials (47 615 patients) were included. SAEs were more common with certolizumab compared with abatacept (rate ratio = 1.58, 95% CI: 1.18, 2.14), adalimumab (1.36, 95% CI: 1.02, 1.81), etanercept (1.60, 95% CI: 1.18, 2.17), golimumab (1.45, 95% CI: 1.00, 2.08), rituximab (1.63, 95% CI: 1.16, 2.30), tofacitinib (1.44, 95% CI: 1.03, 2.02) and control (1.45, 95% CI: 1.13, 1.87); and tocilizumab compared with abatacept (1.30, 95% CI: 1.03, 1.65), etanercept (1.31, 95% CI: 1.04, 1.67) and rituximab (1.34, 95% CI: 1.01, 1.78). No other comparisons were statistically significant. Accounting for study duration confirmed our findings for up to 6 months' treatment but not for longer-term treatment (6-24 months). No differences in mortality between b/ts-DMARDs and control were found. Based on the GRADE approach, confidence in the estimates was low due to lack of head-to-head comparison trials and imprecision in indirect estimates.CONCLUSION: Despite low confidence in the estimates, our analysis found potential differences in rates of SAEs. Our data suggest caution should be taken when deciding among available drugs.SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42014014842

Culturally targeted video improves psychosocial outcomes in latina women at risk of hereditary breast and ovarian cancer

Latina women at risk of hereditary breast and ovarian cancer (HBOC) have lower awareness, knowledge, and use of genetic counseling and testing services (GCT) than non-Latina Whites. Few interventions have been developed to reduce these disparities among at-risk Latinas. This pilot study assessed the impact of a culturally targeted narrative video developed by our team. The study included 40 Latina immigrants living in the United States who were at risk of HBOC, including a ected and una ected women. We assessed pre-post di erences in psychosocial outcomes. Participants were 47.35 years old on average (SD = 9.48). Most (70%) were una ected with cancer, had an annual income of $40,000 or less (65%), an education of High School or less (62.5%), and were uninsured (77.5%). The video significantly enhanced knowledge (p < 0.001), positive attitudes (p < 0.05), anticipatory positive emotions (p < 0.05), and intentions to participate in counseling (p < 0.001). Importantly, the video also significantly reduced negative attitudes (p < 0.05), and attitudinal ambivalence (p < 0.001). The culturally targeted video shows preliminary evidence in improving psychosocial outcomes related to GCT uptake in Latinas at risk for HBOC. This intervention is a promising easily-disseminable strategy to address disparities in GCT utilizationThis research was funded by the National Cancer Institute (R03CA191543; Hurtado-de-Mendoza and Sheppard, MPIs). This project was also supported by Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS) by Federal Funds; the National Center for Advancing Translational Sciences (NCATS); and the National Institutes of Health (NIH), through the Clinical and Translational Science Awards Program (CTSA) (KL2TR001432; Hurtado-de-Mendoza. PI), and by the Ministry of Science, Innovation, and Universities in Spain (PGC2018-093821-B-I00, FEDER, MICINN, Carrera, PI)

Cognitive function prior to systemic therapy and subsequent well‐being in older breast cancer survivors: Longitudinal findings from the Thinking and Living with Cancer Study

ObjectiveTo investigate the relationships between self‐reported and objectively measured cognitive function prior to systemic therapy and subsequent well‐being outcomes over 24 months in older breast cancer survivors.MethodsData were from 397 women aged 60 to 98 diagnosed with non‐metastatic breast cancer in the Thinking and Living with Cancer Study recruited from 2010‐2016. Cognitive function was measured at baseline (following surgery, prior to systemic therapy) using neuropsychological assessments of attention, processing speed, and executive function (APE), learning and memory (LM), and the self‐reported FACT‐Cog scale. Well‐being was measured using the FACT‐G functional, physical, social, and emotional well‐being domain scales at baseline and 12 and 24 months later, scaled from 0 (low) to 100 (high). Linear mixed‐effects models assessed the relationships between each of baseline APE, LM, and FACT‐Cog quartiles with well‐being scores over 24 months, adjusted for confounding variables.ResultsAt baseline, older survivors in the lowest APE, LM, and FACT‐Cog score quartiles experienced poorer global well‐being than those in the highest quartiles. At 24 months, older survivors tended to improve in well‐being, and there were no differences according to baseline APE or LM scores. At 24 months, mean global well‐being was 80.3 (95% CI: 76.2‐84.3) among those in the lowest vs 86.6 (95% CI: 83.1‐90.1) in the highest FACT‐cog quartile, a clinically meaningful difference of 6.3 points (95% CI: 1.5‐11.1).ConclusionsAmong older breast cancer survivors, self‐reported, but not objective cognitive impairments, were associated with lower global well‐being over the first 2 years of survivorship.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155908/1/pon5376.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155908/2/pon5376_am.pd

Pre-treatment psychoneurological symptoms and their association with longitudinal cognitive function and quality of life in older breast cancer survivors

Context Symptoms affect quality of life (QOL), functional status, and cognitive function in cancer survivors, but older survivors are understudied. Objectives To identify prototypical pre-systemic therapy psychoneurological symptom clusters among older breast cancer survivors, and determine whether these symptom clusters predicted cognition and QOL over time. Methods Women with newly diagnosed non-metastatic breast cancer (n=319) and matched non-cancer controls (n=347) aged 60+ completed questionnaires and neuropsychological tests before systemic therapy and 12- and 24-months later. Latent class analysis identified clusters of survivors based upon their pre-therapy depression, anxiety, fatigue, sleep disturbance, and pain. Linear mixed-effects models examined changes in objective cognition, perceived cognition, and functional status (instrumental activities of daily living (IADL) disability, functional well-being, and breast cancer-specific QOL) by group, controlling for covariates. Results Nearly one-fifth of older survivors were classified as having a high pre-therapy symptoms (n=51; 16%); the remainder had a low symptoms (n=268; 84%); both groups improved over time on all outcomes. However, compared to the low symptom group and controls, survivors with high symptoms had lower baseline objective cognition and lower perceived cognition at baseline and 24-months, lower functional well-being at baseline and 12-months, greater IADL disability at baseline, and lower breast cancer-specific QOL at all time points (all p<0.05). Conclusion Nearly one-fifth of older breast cancer survivors had high psychoneurological symptoms at diagnosis, which, predict clinically meaningful decrements in perceived cognition and function in the first 24 months post-diagnosis. Pre-treatment psychoneurological symptom clusters could identify survivors for monitoring or intervention

Symptom burden among older breast cancer survivors: The Thinking and Living With Cancer (TLC) study

Background: Little is known about longitudinal symptom burden and its consequences for well-being, and if lifestyle moderates burden in older survivors. Methods: We report on 36-month data from survivors 60+ with newly diagnosed non-metastatic breast cancer and non-cancer controls recruited August 2010-June 2016. Symptom burden was a sum of self-reported symptoms/diseases: pain (yes/no), fatigue (FACT-fatigue), cognitive (FACT-cog), sleep problems (yes/no), depression (CES-D), anxiety (STAI), and cardiac problems and neuropathy (yes/no). Well-being was measured using the FACT-G, scaled from 0–100. Lifestyle included smoking, alcohol use, BMI, physical activity, and leisure activities. Mixed models assessed relationships between treatment group (chemotherapy +/− hormonal, hormonal only, control) and symptom burden, lifestyle, and covariates. Separate models tested the effects of fluctuations in symptom burden and lifestyle on function. Results: All groups reported high baseline symptoms, and levels remained high over time; survivor-control differences were most notable for cognitive and sleep problems, anxiety, and neuropathy. The adjusted burden score was highest among chemotherapy-exposed survivors, followed by hormonal therapy vs. controls (p<.001). Burden score was related to physical, emotional, and functional well-being (e.g., survivors with lower vs. higher burden scores had 12.4-point higher physical well-being score). The composite lifestyle score was not related to symptom burden or well-being, but physical activity was significantly associated with each outcome (<.005). Conclusions: Cancer and its treatments are associated with a higher level of actionable symptoms and greater loss of well-being over time in older breast cancer survivors than comparable non-cancer populations, suggesting the need for surveillance and opportunities for intervention