The effect of COVID-19 pandemic on healthcare seeking in an urban informal settlement in Nairobi and a rural setting in western Kenya

The COVID-19 pandemic caused widespread changes and disruptions to healthcare seeking behavior. There are limited studies on the effect of the COVID-19 pandemic on healthcare seeking patterns in low-and middle-income countries (LMICs), especially in settings with inequitable access to healthcare in rural and urban informal settlements. We investigated the effect of the COVID-19 pandemic on reported healthcare seeking at health facilities and chemists using morbidity data from participants in an ongoing population-based infectious disease surveillance platform in Asembo in Siaya County, a rural setting in western Kenya and Kibera, an urban informal settlement in Nairobi County. We described healthcare seeking patterns before (from 1st January 2016 to 12th March 2020) and during the pandemic (from 13th March 2020 to 31st August 2022) by gender and age for any reported illness and select clinical syndromes using frequencies and percentages. We used a generalized estimating equation with an exchangeable correlation structure to assess the effect of the pandemic on healthcare seeking adjusting for gender and age. Overall, there was a 19% (adjusted odds ratio, aOR: 0.81; 95% Confidence Interval, CI: 0.79-0.83) decline in odds of seeking healthcare at health facilities for any illness in Asembo during the pandemic, and a 30% (aOR: 0.70; 95% CI: 0.67-0.73) decline in Kibera. Similarly, there was a decline in seeking healthcare by clinical syndromes, e.g., for ARI, aOR: 0.76; 95% CI:0.73-0.79 in Asembo, and aOR: 0.68; 95% CI:0.64-0.72 in Kibera. The pandemic resulted in increased healthcare seeking at chemists (aOR: 1.23; 95% CI: 1.20-1.27 in Asembo, and aOR: 1.40; 95% CI: 1.35-1.46 in Kibera). This study highlights interruptions to healthcare seeking in resource-limited settings due to the COVID-19 pandemic. The pandemic resulted in a substantial decline in seeking care at health facilities, and an increase of the same at chemists.

Seroconversion and seroprevalence of TORCH infections in a pregnant women cohort study, Mombasa, Kenya, 2017-2019

Women infected during pregnancy with TORCH (Toxoplasmosis, Other, Rubella, Cytomegalovirus, and Herpes simplex viruses) pathogens have a higher risk of adverse birth outcomes including stillbirth / miscarriage because of mother-to-child transmission. To investigate these risks in pregnant women in Kenya, we analyzed serum specimens from a pregnancy cohort study at three healthcare facilities. A sample of 481 participants was selected for TORCH pathogen antibody testing to determine seroprevalence. A random selection of 285 from the 481 participants was selected to measure seroconversion. These sera were tested using an IgG enzyme-linked immunosorbent assay against 10 TORCH pathogens. We found that the seroprevalence of all but three of the 10 TORCH pathogens at enrollment was >30%, except for Bordetella pertussis (3.8%), Treponema pallidum (11.4%), and varicella zoster virus (0.5%). Conversely, very few participants seroconverted during their pregnancy and were herpes simplex virus type 2 (n = 24, 11.2%), parvovirus B19 (n = 14, 6.2%), and rubella (n = 12, 5.1%). For birth outcomes, 88% of the participant had live births and 12% had stillbirths or miscarriage. Cytomegalovirus positivity at enrolment had a statistically significant positive association with a live birth outcome (p = 0.0394). Of the 10 TORCH pathogens tested, none had an association with adverse pregnancy outcome.

Correcting for measurement error in assessing gestational age in a low-resource setting: a regression calibration approach

Introduction

Measurement error in gestational age (GA) may bias the association of GA with a health outcome. Ultrasound-based GA is considered the gold standard and is not readily available in low-resource settings. We corrected for measurement error in GA based on fundal height (FH) and date of last menstrual period (LMP) using ultrasound from the sub-cohort and adjusted for the bias in associating GA with neonatal mortality and low birth weight (< 2,500 grams, LBW).

Methods

We used data collected from 01/2015 to 09/2019 from pregnant women enrolled at two public hospitals in Siaya county, Kenya (N = 2,750). We used regression calibration to correct for measurement error in FH- and LMP-based GA accounting for maternal and child characteristics. We applied logistic regression to associate GA with neonatal mortality and low birth weight, with and without calibrating FH- and LMP-based GA.

Results

Calibration improved the precision of LMP (correlation coefficient, ρ from 0.48 to 0.57) and FH-based GA (ρ from 0.82 to 0.83). Calibrating FH/LMP-based GA eliminated the bias in the mean GA estimates. The log odds ratio that quantifies the association of GA with neonatal mortality increased by 29% (from -0.159 to -0.205) by calibrating FH-based GA and by more than twofold (from -0.158 to -0.471) by calibrating LMP-based GA.

Conclusion

Calibrating FH/LMP-based GA improved the accuracy and precision of GA estimates and strengthened the association of GA with neonatal mortality/LBW. When assessing GA, neonatal public health and clinical interventions may benefit from calibration modeling in settings where ultrasound may not be fully available.

Heterogenous transmission and seroprevalence of SARS-CoV-2 in two demographically diverse populations with low vaccination uptake in Kenya, March and June 2021

Background

SARS-CoV-2 has extensively spread in cities and rural communities, and studies are needed to quantify exposure in the population. We report seroprevalence of SARS-CoV-2 in two well-characterized populations in Kenya at two time points. These data inform the design and delivery of public health mitigation measures.

Methods

Leveraging on existing population based infectious disease surveillance (PBIDS) in two demographically diverse settings, a rural site in western Kenya in Asembo, Siaya County, and an urban informal settlement in Kibera, Nairobi County, we set up a longitudinal cohort of randomly selected households with serial sampling of all consenting household members in March and June/July 2021. Both sites included 1,794 and 1,638 participants in the March and June/July 2021, respectively. Individual seroprevalence of SARS-CoV-2 antibodies was expressed as a percentage of the seropositive among the individuals tested, accounting for household clustering and weighted by the PBIDS age and sex distribution.

Results

Overall weighted individual seroprevalence increased from 56.2% (95%CI: 52.1, 60.2%) in March 2021 to 63.9% (95%CI: 59.5, 68.0%) in June 2021 in Kibera. For Asembo, the seroprevalence almost doubled from 26.0% (95%CI: 22.4, 30.0%) in March 2021 to 48.7% (95%CI: 44.3, 53.2%) in July 2021. Seroprevalence was highly heterogeneous by age and geography in these populations-higher seroprevalence was observed in the urban informal settlement (compared to the rural setting), and children aged <10 years had the lowest seroprevalence in both sites. Only 1.2% and 1.6% of the study participants reported receipt of at least one dose of the COVID-19 vaccine by the second round of serosurvey-none by the first round.

Conclusions

In these two populations, SARS-CoV-2 seroprevalence increased in the first 16 months of the COVID-19 pandemic in Kenya. It is important to prioritize additional mitigation measures, such as vaccine distribution, in crowded and low socioeconomic settings.

Estimating excess mortality during the COVID-19 pandemic from a population-based infectious disease surveillance in two diverse populations in Kenya, March 2020-December 2021

Robust data on the impact of the COVID-19 pandemic on mortality in Africa are relatively scarce. Using data from two well-characterized populations in Kenya we aimed to estimate excess mortality during the COVID-19 pandemic period. The mortality data arise from an ongoing population-based infectious disease surveillance (PBIDS) platform, which has been operational since 2006 in rural western Kenya (Asembo, Siaya County) and an urban informal settlement (Kibera, Nairobi County), Kenya. PBIDS participants were regularly visited at home (2-3 times a year) by field workers who collected demographic data, including deaths. In addition, verbal autopsy (VA) interviews for all identified deaths are conducted. We estimated all-cause and cause-specific mortality rates before and during the height of the COVID-19 pandemic, and we compared associated mortality rates between the periods using incidence rate ratios. Excess deaths during the COVID-19 period were also estimated by modelling expected deaths in the absence of COVID-19 by applying a negative binomial regression model on historical mortality data from January 2016. Overall and monthly excess deaths were determined using the P-score metric. Spearman correlation was used to assess whether there is a relationship between the generated P-score and COVID-19 positivity rate. The all-cause mortality rate was higher during the COVID-19 period compared to the pre-COVID-19 period in Asembo [9.1 (95% CI, 8.2-10.0) vs. 7.8 (95% CI, 7.3-8.3) per 1000 person-years of observation, pyo]. In Kibera, the all-cause mortality rate was slightly lower during the COVID-19 period compared to the pre-COVID-19 period [2.6 (95% CI, 2.2-3.2 per 1000 pyo) vs. 3.1; 95% CI, 2.7-3.4 per 1000 pyo)]. An increase in all-cause mortality was observed (incidence rate ratio, IRR, 1.16; 95% CI, 1.04-1.31) in Asembo, unlike in Kibera (IRR, 0.88; 95% CI, 0.71-1.09). The notable increase in mortality rate in Asembo was observed among persons aged 50 to 64 years (IRR, 2.62; 95% CI, 1.95-3.52), persons aged 65 years and above (5.47; 95% CI, 4.60-6.50) and among females (IRR, 1.25; 95% CI, 1.07-1.46). These age and gender differences were not observed in Kibera. We observed an increase in the mortality rate due to acute respiratory infection, including pneumonia (IRR, 1.45;95% CI, 1.03-2.04), and a reduction in the mortality rate due to pulmonary tuberculosis (IRR, 0.22; 95% CI, 0.05-0.87) among older children and adults in Asembo. There was no statistically significant change in mortality rates due to leading specific causes of death in Kibera. Overall, during the COVID-19 period observed deaths were higher than expected deaths in Asembo (P-score = 6.0%) and lower than expected in Kibera (P-score = -22.3%).Using well-characterized populations in the two diverse geographic locations, we demonstrate a heterogenous impact of the COVID-19 pandemic on all-cause and cause-specific mortality rates in Kenya. We observed more deaths than expected during the COVID-19 period in our rural site in western Kenya contrary to the urban site in Nairobi, the capital city in Kenya.

Dynamic Incidence of Typhoid Fever over a 10-Year Period (2010-2019) in Kibera, an Urban Informal Settlement in Nairobi, Kenya

Typhoid fever burden can vary over time. Long-term data can inform prevention strategies; however, such data are lacking in many African settings. We reexamined typhoid fever incidence and antimicrobial resistance (AMR) over a 10-year period in Kibera, a densely populated urban informal settlement where a high burden has been previously described. We used data from the Population Based Infectious Diseases Surveillance platform to estimate crude and adjusted incidence rates and prevalence of AMR in nearly 26,000 individuals of all ages. Demographic and healthcare-seeking information was collected through household visits. Blood cultures were processed for patients with acute fever or lower respiratory infection. Between 2010 and 2019, 16,437 participants were eligible for blood culture and 11,848 (72.1%) had a culture performed. Among 11,417 noncontaminated cultures (96.4%), 237 grew Salmonella enterica serovar Typhi (2.1%). Overall crude and adjusted incidences were 95 and 188 cases per 100,000 person-years of observation (pyo), respectively. Annual crude incidence varied from 144 to 233 between 2010 and 2012 and from 9 to 55 between 2013 and 2018 and reached 130 per 100,000 pyo in 2019. Children 5-9 years old had the highest overall incidence (crude, 208; adjusted, 359 per 100,000 pyo). Among isolates tested, 156 of 217 were multidrug resistant (resistant to chloramphenicol, ampicillin, and trimethoprim/sulfamethoxazole [71.9%]) and 6 of 223 were resistant to ciprofloxacin (2.7%). Typhoid fever incidence resurged in 2019 after a prolonged period of low rates, with the highest incidence among children. Typhoid fever control measures, including vaccines, could reduce morbidity in this setting.

Associations of Midlife Dietary Patterns with Incident Dementia and Brain Structure: Findings from the UK Biobank Study

BACKGROUND

At present, the results on the associations between dietary patterns and the risk of dementia are inconsistent, and studies on the associations between dietary patterns and brain structures are limited.

OBJECTIVE

We aimed to investigate the associations of midlife dietary patterns with incident dementia and brain structures.

METHODS

Based on the UK Biobank Study, we investigated the 1) prospective associations of four healthy dietary pattern indices (healthy plant-based diet index [hPDI], Mediterranean diet score [MDS], Recommended food score [RFS], and Mediterranean-Dietary Approaches to Stop Hypertension Intervention [DASH] Intervention for Neurodegenerative Delay Diet [MIND]) with incident dementia (identified using linked hospital data; N = 114,684; mean age, 56.8 years; 55.5% females) using Cox proportional-hazards regressions and the 2) cross-sectional associations of these dietary pattern indices with brain structures (estimated using magnetic resonance imaging; N = 18,214; mean age, 55.9 years; 53.1% females) using linear regressions. A series of covariates were adjusted, and several sensitivity analyses were conducted.

RESULTS

A total of 481 (0.42%) participants developed dementia during the average 9.4-year follow-up. Although the associations were not statistically significant, all dietary patterns exerted protective effects against incident dementia (all hazard ratios < 1). Furthermore, higher dietary pattern indices were significantly associated with larger regional brain volumes, including volumes of gray matter in the parietal and temporal cortices and volumes of the hippocampus and thalamus. The main results were confirmed via sensitivity analyses.

CONCLUSIONS

Greater adherence to hPDI, MDS, RFS, and MIND was individually associated with larger brain volumes in specific regions. This study shows a comprehensive picture of the consistent associations of midlife dietary patterns with the risk of dementia and brain health, underscoring the potential benefits of a healthy diet in the prevention of dementia.

A multivariate joint model to adjust for random measurement error while handling skewness and correlation in dietary data in an epidemiologic study of mortality

PURPOSE

A substantial proportion of global deaths is attributed to unhealthy diet, which can be assessed at baseline or longitudinally. We demonstrated how to simultaneously correct for random measurement error, correlations, and skewness in the estimation of associations between dietary intake and all-cause mortality.

METHODS

We applied a multivariate joint model (MJM) that simultaneously corrected for random measurement error, skewness, and correlation among longitudinally measured intake levels of cholesterol, total fat, dietary fiber, and energy with all-cause mortality using US National Health and Nutrition Examination Survey linked to the National Death Index mortality data. We compared MJM with the mean method that assessed intake levels as the mean of a person's intake.

RESULTS

The estimates from MJM were larger than those from the mean method. For instance, the logarithm of hazard ratio (log HR) for dietary fiber intake increased by 14 times (from -0.04 to -0.60) with the MJM method. This translated into relative hazard of death of 0.55 (95% Credible Interval, CI: 0.45, 0.65) with the MJM and 0.96 (95% CI: 0.95, 0.97) with the mean method.

CONCLUSIONS

MJM adjusts for random measurement error and flexibly addresses correlations and skewness among longitudinal measures of dietary intake when estimating their associations with death.

Weight change across adulthood and accelerated biological aging in middle-aged and older adults

BACKGROUND

Little is known regarding the association between weight change and accelerated aging.

OBJECTIVES

This study aimed to estimate the influence of weight change across adulthood on biological aging acceleration in middle-aged and older adults in the United States.

METHODS

We used data of 5553 adults (40-84 y) from the National Health and Nutrition Examination Survey 1999-2010. Weight change patterns (i.e., stable normal, maximal overweight, obese to nonobese, nonobese to obese, and stable obese) and absolute weight change groups across adulthood (i.e., from young to middle adulthood, young to late adulthood, and middle to late adulthood) were defined. A biological aging measure (i.e., phenotypic age acceleration [PhenoAgeAccel]) at late adulthood was calculated. Survey analysis procedures with the survey weights were performed.

RESULTS

Across adulthood, maximal overweight, nonobese to obese, and stable obesity were consistently associated with higher PhenoAgeAccel. For instance, from young to middle adulthood, compared with participants who had stable normal weight, participants experiencing maximal overweight, moving from the nonobese to obese, and maintaining obesity had 1.71 (standard error [SE], 0.21; P < 0.001), 3.62 (SE, 0.28; P < 0.001), and 6.61 (SE, 0.58; P < 0.001) higher PhenoAgeAccel values, respectively. From young to middle adulthood, relative to absolute weight loss or gain of <2.5 kg, weight loss of ≥2.5 kg was marginally associated with lower PhenoAgeAccel (P = 0.054), whereas an obese to nonobese pattern from middle to late adulthood was associated with higher PhenoAgeAccel (P < 0.001).

CONCLUSIONS

Maximal overweight, nonobese to obese, and stable obesity across adulthood, as well as an obese to nonobese pattern from middle to late adulthood, were associated with accelerated biological aging. In contrast, weight loss from young to middle adulthood was associated with decelerated biological aging. The findings highlight the potential role of weight management across adulthood for aging. Monitoring weight fluctuation may help identify the population at high risk of accelerated aging.

Modeling of correlated cognitive function and functional disability outcomes with bounded and missing data in a longitudinal aging study

Longitudinal studies of correlated cognitive and disability outcomes among older adults are characterized by missing data due to death or loss to follow-up from deteriorating health conditions. The Mini-Mental State Examination (MMSE) score for assessing cognitive function ranges from a minimum of 0 (floor) to a maximum of 30 (ceiling). To study the risk factors of cognitive function and functional disability, we propose a shared parameter model to handle missingness, correlation between outcomes, and the floor and ceiling effects of the MMSE measurements. The shared random effects in the proposed model handle missingness (either missing at random or missing not at random) and correlation between these outcomes, while the Tobit distribution handles the floor and ceiling effects of the MMSE measurements. We used data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and a simulation study. By ignoring the MMSE floor and ceiling effects in the analyses of the CLHLS, the association of systolic blood pressure with cognitive function was not significant and the association of age with cognitive function was lower by 16.6% (from -6.237 to -5.201). By ignoring the MMSE floor and ceiling effects in the simulation study, the relative bias in the estimated association of female gender with cognitive function was 43 times higher (from -0.01 to -0.44). The estimated associations obtained with data missing at random were smaller than those with data missing not at random, demonstrating how the missing data mechanism affects the analytic results. Our work underscores the importance of proper model specification in longitudinal analysis of correlated outcomes subject to missingness and bounded values.

Persons with dementia and informal caregivers prioritizing care: A mixed-methods study

INTRODUCTION

More persons with dementia are residing in the community as many countries shift from residential care to home and community care. Although there are many forms of care and support available to avoid crisis situations and prolong community living, it remains unclear how these are valued by community-dwelling persons with dementia and their informal caregivers. Understanding perspectives of persons with dementia and informal caregivers on care characteristics is a vital step in valuing care services. This study aims to prioritize care characteristics for community-dwelling persons with dementia and informal caregivers with the use of an innovative mixed-methods approach.

METHODS

Six mixed focus groups were conducted in The Netherlands with persons with dementia (n = 23) and informal caregivers (n = 20), including a quantitative ranking exercise that prioritized seven care and support characteristics from "most important" to "least important," followed by a group discussion about the prioritization. Audio recordings were transcribed and analyzed using thematic analysis.

RESULTS

The ranking exercise and discussion showed that persons with dementia favored in-home care, help with daily activities, and social activities, whereas informal caregivers favored social activities, information about dementia, navigating the health care system, and emotional support.

DISCUSSION

Persons with dementia prioritized day-to-day activities, whereas informal caregivers preferred assistance with organizing care and coping with caregiving. This study created a method to capture the care preferences of persons with dementia and informal caregivers.

A machine-learning modified CART algorithm informs Merkel cell carcinoma prognosis

BACKGROUND

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer with a high mortality rate. MCC staging is currently based on tumour primary size, clinical detectability of lymph node metastases, performance of a lymph node biopsy, and presence of distant metastases.

OBJECTIVE

We aimed to use a modified classification and regression tree (CART) algorithm using available data points in the National Cancer Database (NCDB) to elucidate novel prognostic factors for MCC.

METHODS

Retrospective cohort study of the NCDB and Surveillance, Epidemiology, and End Results (SEER) registries. Cases from the NCDB were randomly assigned to either the training or validation cohorts. A modified CART algorithm was created with data from the training cohort and used to identify prognostic groups that were validated in the NCDB validation and SEER cohorts.

RESULTS

A modified CART algorithm using tumour variables available in the NCDB identified prognostic strata as follows: I: local disease, II: ≤3 positive nodes, III: ≥4 positive nodes, and IV: presence of distant metastases. Three-year survival for these groups in the NCDB validation cohort were 81.2% (SE: 1.7), 59.6% (SE: 3.0), 38.0% (SE: 6.0), and 20.2% (SE: 7.0), respectively. These strata were exhibited greater within-group homogeneity than AJCC groups and were more predictive of survival.

CONCLUSIONS

Risk-stratified grouping of MCC patients incorporating positive lymph node count were strongly predictive of survival and demonstrated a high degree of within-group homogeneity and survival prediction. Incorporation of positive lymph node count within overall staging or sub-staging may help to improve future MCC staging criteria.

Comparison of Survival After Mohs Micrographic Surgery vs Wide Margin Excision for Early-Stage Invasive Melanoma

Importance

Melanoma is among the most common malignant neoplasms in the United States, with 91 270 cases estimated to be diagnosed in 2018. Since 2012, Mohs micrographic surgery (MMS) has gained popularity in the treatment of melanoma in situ. Although current guidelines for invasive melanoma without nodal metastases recommend surgery with wide margin excision (WME), use of MMS for this disease has increased as well, particularly in early stages. How the survival outcomes after each procedure compare with one another for early-stage invasive melanoma is unknown to date.

Objective

To evaluate overall survival of patients with stage I melanoma defined by the American Joint Committee on Cancer Cancer Staging Manual, 8th edition (AJCC-8) after MMS vs traditional WME.

Design, Setting, and Analysis

This retrospective cohort study includes all patients with AJCC-8 stage I melanoma who underwent MMS or WME in the National Cancer Database with a diagnosis from January 1, 2004, through December 31, 2014. The National Cancer Database includes all reportable cases from Commission on Cancer-accredited facilities and represents approximately 50% of all newly diagnosed melanoma cases in the United States. Data were analyzed from November 13, 2018, through June 9, 2019.

Exposures

MMS vs WME.

Main Outcomes and Measures

Overall survival evaluated using multivariable Cox proportional hazards regression analysis.

Results

A total of 70 319 eligible patients (52.3% male and 47.7% female; median [SD] age, 57.0 [16.2] years) were identified, including 67 085 treated with WME and 3234 treated with MMS. Multivariable Cox proportional hazards regression survival analysis controlling for clinical and tumor factors revealed that treatment with MMS was associated with a modest improvement in overall survival relative to WME (hazard ratio [HR], 0.86; 95% CI, 0.76-0.97). Propensity score-matched analysis of cohorts of patients treated with MMS vs WME also found modestly improved survival for those treated with MMS (HR, 0.82; 95% CI, 0.68-0.98). Academic facilities were more likely to use MMS than nonacademic facilities (odds ratio, 2.03; 95% CI, 1.88-2.18).

Conclusions and Relevance

These findings suggest that Mohs surgery may provide an alternative approach to traditional WME for appropriately selected cases of AJCC-8 stage I melanoma without compromising patient survival.

Personalized and typical concurrent risk of limitations in social activity and mobility in older persons with multiple chronic conditions and polypharmacy

PURPOSE

We define personalized concurrent risk (PCR) as the subject-specific probability of an index outcome within a defined interval of time, while currently at risk for a separate outcome, where the outcomes are not mutually exclusive and can be jointly modeled with a shared random intercept. We further define typical concurrent risk as the risk obtained by setting the random intercept to null.

METHODS

Drawing data from the Medical Expenditure Panel Survey (cohorts 2008-2013), we jointly model limitations in social activity and mobility over two years among older community-dwelling persons with both hypertension and chronic obstructive pulmonary disease. The joint model uses inverse probability of treatment weighting based on each participant's baseline propensity of polypharmacy (≥5 classes of medication).

RESULTS

Even among participants with the same covariates, older persons with multiple chronic conditions exhibit wide-ranging heterogeneity of the treatment effect from polypharmacy, a risk factor for negative health outcomes among older persons. The magnitude of the PCRs is dominated by the value of the subject-specific random effect.

CONCLUSIONS

Estimates of PCR and typical concurrent risk can be calculated from national or institutional data sets and may facilitate the practice of personalized care for older patients with multiple chronic conditions.

The Impact of Dementia Diagnosis on Patterns of Potentially Inappropriate Medication Use Among Older Adults

Background

Use of potentially inappropriate medications (PIM) among people with dementia is common. We assessed the patterns of medication use from 1-year before dementia diagnosis, to 1-year after dementia diagnosis, compared with patterns of medication use in people without dementia.

Methods

We conducted longitudinal study using the National Alzheimer's Coordinating Center data. Adults aged 65 years and older newly diagnosed with dementia (n = 2,418) during 2005-2015 were year, age, and sex matched 1:1 with controls. Generalized estimating equation models weighted for missingness and adjusted for 15 participant characteristics were fit.

Results

Among participants with dementia, number of medications reported 1-year prediagnosis was 8% lower than at diagnosis year (p < .0001) and 11% higher 1-year postdiagnosis compared with year of diagnosis (p < .0001). Among participants with dementia, the odds of PIM exposure, assessed using the 2015 Beers Criteria, was 17% lower 1-year prediagnosis (p < .0001) and 17% higher 1-year postdiagnosis (p = .006) compared with year of diagnosis. Among controls, there were approximately 6% more medications reported between consecutive years (p < .0001 each comparison) and the odds of PIM exposure increased 11% between consecutive years (p = .006 and p = .047). At each annual follow-up, participants with dementia had lower odds of PIM exposure than their controls (prediagnosis p < .0001, at diagnosis p = .0007, postdiagnosis p = .03, respectively). There were no differences in exposure to anticholinergic medications.

Conclusions

Number of medications and PIM use increased annually for participants with and without dementia. Persistent challenge of increasing PIM use in this group of older adults is of major concern and warrants interventions to minimize such prescribing.

Substance P and fibrotic diseases

Substance P (SP) is an undecapeptide encoding the tachykinin 1 (TAC1) gene and belongs to the tachykinin family. SP is widely distributed in the central nervous system and the peripheral nervous system. SP is also produced by nonneuronal cells, such as inflammatory cells and endothelial cells. The biological activities of SP are mainly regulated through the high-affinity neurokinin 1 receptor (NK-1R). The SP/NK-1R system plays an important role in the molecular bases of many human pathophysiologic processes, such as pain, infectious and inflammatory diseases, and cancer. In addition, this system has been implicated in fibrotic diseases and processes such as wound healing, myocardial fibrosis, bowel fibrosis, myelofibrosis, renal fibrosis, and lung fibrosis. Recently, studies have shown that SP plays an important role in liver fibrosis and that NK-1R antagonists can inhibit the progression of fibrosis. NK-1R receptor antagonists could provide clinical solutions for fibrotic diseases. This review summarizes the structure and function of SP and its involvement in fibrotic diseases.

Evaluation of Lymph Node Ratio Association With Long-term Patient Survival After Surgery for Node-Positive Merkel Cell Carcinoma

Importance

Merkel cell carcinoma (MCC) carries the highest mortality rate among cutaneous cancers and is rapidly rising in incidence. Identification of prognostic indicators may help guide patient counseling and treatment planning. Lymph node ratio (LNR), the ratio of positive lymph nodes to the total number of examined lymph nodes, is an established prognostic indicator in other cancers.

Objectives

The primary objective was to evaluate the association between LNR and patient survival after surgery for node-positive MCC. The secondary objective was to evaluate whether the survival rates associated with adjuvant therapies vary by patient LNR status.

Design, Setting, and Participants

Retrospective cohort study of patients with node-positive MCC treated with surgery and lymphadenectomy. We queried the National Cancer Database (NCDB) and the Surveillance, Epidemiology, and End Results (SEER) registry for patient records. Data originated from 2004 through 2017 for the NCDB and from 1973 through 2016 for the SEER registry. The SEER registry comprises a population-based US cohort while cases from the NCDB include all reportable cases from Commission on Cancer-accredited facilities and represents approximately 70% of all newly diagnosed cancers in the United States. All data analysis took place between August 1, 2018, and February 11, 2019.

Exposures

The ratio of positive lymph nodes to the total number of examined lymph nodes, LNR, was stratified into quartiles.

Main Outcomes and Measures

Overall survival (NCDB) and disease-specific survival (SEER).

Results

We identified 736 eligible cases in the NCDB and 538 eligible cases in the SEER registry. Among these 1274 patients, the mean (SD) age was 71.1 (11.5) years, and 401 (31.5%) were women. After controlling for clinical and tumor factors including AJCC N staging, patient LNR of 0.07 to 0.31 (hazard ratio [HR], 1.37; 95% CI, 1.03-1.81) and greater than 0.31 (HR, 2.84; 95% CI, 2.10-3.86) was associated with significantly worse survival than an LNR less than 0.07. Univariate supplementary analysis performed in the SEER data set revealed a similar association of LNR with disease-specific survival. For patients with an LNR greater than 0.31, treatment with surgery and adjuvant chemoradiation therapy was associated with improved survival compared with surgery and adjuvant radiation therapy alone (HR, 0.61; 95% CI, 0.38-0.97), while this was not found for patients with an LNR of 0.31 or lower (HR, 0.93; 95% CI, 0.65-1.33).

Conclusions and Relevance

For lymph node-positive MCC, LNR offers a potentially prognostic metric alongside traditional TNM staging that may be useful for both patient counseling and treatment planning after surgery.

Joint modeling of concurrent binary outcomes in a longitudinal observational study using inverse probability of treatment weighting for treatment effect estimation

PURPOSE

Correlated healthcare utilization outcomes may be encoded as binary outcomes in epidemiologic studies. We demonstrate how to account for correlation between concurrent binary outcomes and confounding by person characteristics when estimating a treatment effect in observational studies.

METHODS

We present a joint shared-parameter model, weighted by inverse probability of treatment weights (IPTW) to account for confounding. The model is evaluated in a simulation study that emulates the Medical Expenditure Panel Survey data and compared with a covariate-adjusted joint model and with separate outcome models (IPTW weighted and covariate adjusted).

RESULTS

For the IPTW-weighted joint model, relative bias in the estimated treatment effect on outcome 1 ranged from -0.057 to -0.033 and outcome 2 from -0.077 to -0.043. For the covariate-adjusted joint model, relative bias ranged from -0.010 to -0.083 for outcome 1 and from -0.087 to -0.110 for outcome 2. The covariate-adjusted joint model estimated the effect more closely than the covariate-adjusted separate model. The IPTW-weighted joint model estimated the effect more closely for outcome 1.

CONCLUSIONS

The IPTW-weighted joint model handles correlation between binary outcomes, adjusts for confounding, and estimates the treatment effect accurately in observational studies. We illustrate the contribution of person-specific effects in estimating personalized risk.

Sociodemographic Factors and Characteristics of Caregivers as Determinants of Skilled Nursing Facility Admissions When Modeled Jointly With Functional Limitations

OBJECTIVES

We examined whether previously identified relationships between sociodemographic factors and caregivers for skilled nursing facility (SNF) admissions are replicated when jointly accounting for longitudinal change in functional limitations. We further explored the impact of caregivers by investigating the relationship between caregiver's characteristics and SNF admissions.

DESIGN

Longitudinal follow-up study.

SETTING

The United States of America.

PARTICIPANTS

In total, 3875 older Americans from the 2011-2015 rounds of the National Health and Aging Trends Study linked with Centers for Medicare and Medicaid Services.

MEASURES

Sociodemographic factors and caregiver's characteristics were used to predict change in functional limitations from baseline and time to first SNF admission using a joint modeling approach.

RESULTS

In total, 11.3% of the study population had a SNF admission during follow-up. For sociodemographic factors, non-Hispanic white, <9th grade education, and having at least 1 caregiver were associated with higher hazards of SNF admission than other race/ethnicity, college or higher education, and no caregiver, respectively. In contrast, living with a partner or living with others was associated with lower hazard of SNF admissions. For characteristics of caregivers, medical-supportive caregiver was associated with increased hazard of SNF admissions, whereas partner caregiver was protective of SNF admissions. Jointly modeling SNF admissions and change in functional limitations resulted in greater precision of effect estimates than modeling these outcomes separately.

CONCLUSIONS AND IMPLICATIONS

The study provides insight that can help identify high-risk populations for future interventions to prevent or delay SNF admissions. The relation between caregivers and SNF admissions depended on caregiver's characteristics. Future work should focus on providing help to those without a partner caregiver or needing help managing their health to ensure independent living and improve the well-being of older adults. Precision increased when jointly modeling the SNF admission with change in functional limitations.

Meal analysis for understanding eating behavior: meal- and participant-specific predictors for the variance in energy and macronutrient intake

Background

Meals differ in their nutritional content. This variation has not been fully addressed despite its potential contribution in understanding eating behavior. The aim of this study was to investigate the between-meal and between-individual variance in energy and macronutrient intake as a measure of variation in intake and the meal type-specific relative importance of predictors of these intake variations.

Methods

Energy and macronutrient intake were derived from three 24 h dietary recalls in an EPIC-Potsdam sub-cohort of 814 German adults. Intra-class correlation was calculated for participants and meal type. Predictors of intake were assessed using meal type-specific multilevel regression models in a structural equation modeling framework at intake and participant levels using the Pratt Index. The importance of the predictor energy misreporting was assessed in sensitivity analyses on 682 participants. 95% confidence intervals were calculated based on 1000 bootstrap samples.

Results

Differences between meal types explain a large proportion of the variation in intake (intra-class correlation: 39% for energy, 25% for carbohydrates, 47% for protein, and 33% for fat). Between-participant variation in intake was much lower, with a maximum of 3% for carbohydrate and fat. Place of meal was the most important intake-level predictor of energy and macronutrient intake (Pratt Index of up to 65%). Week/weekend day was important in the breakfast meal, and prior interval (hours passed since last meal) was important for the afternoon snack and dinner. On the participant level, sex was the most important predictor, with Pratt Index of up to 95 and 59% in the main and in the sensitivity analysis, respectively. Energy misreporting was especially important at the afternoon snack, accounting for up to 69% of the explained variance.

Conclusions

The meal type explains the highest variation in energy and macronutrient intakes. We identified key predictors of variation in the intake and in the participant levels. These findings suggest that successful dietary modification efforts should focus on improving specific meals.

Electronic supplementary material

The online version of this article (10.1186/s12937-019-0440-8) contains supplementary material, which is available to authorized users.

Treatment of primary nonmetastatic melanoma at high-volume academic facilities is associated with improved long-term patient survival

BACKGROUND

Previous studies of cancer care have demonstrated improved long-term patient outcomes for those treated at high-volume centers. The influence of treatment center characteristics on outcomes for primary nonmetastatic melanoma is not currently established.

OBJECTIVE

We aimed to investigate the association of cancer treatment center case volume and academic affiliation with long-term patient survival for cases of primary nonmetastatic melanoma.

METHODS

Cases of melanoma diagnosed in US adults from 2004 to 2014 and included in the National Cancer Database were identified. Hospitals were grouped by yearly case-volume quartile: bottom quartile, 2 middle quartiles, and top quartile.

RESULTS

Facility case volume was significantly associated with long-term patient survival (P < .0001). The 5-year survival rates were 76.8%, 81.9%, and 86.4% for patients treated at institutions in the bottom, middle, and top quartiles of case volume, respectively. On multivariate analysis, treatment at centers in both middle quartiles (hazard ratio, 0.834; 95% confidence interval, 0.778-0.895) and in the top quartile (hazard ratio, 0.691; 95% confidence interval, 0.644-0.741) of case volume was associated with improved survival relative to that of patients treated at hospitals in the bottom quartile of case volume. Academic affiliation was associated with improved outcomes for top-quartile- but not middle-quartile-volume facilities.

LIMITATIONS

Disease-specific survival was not available.

CONCLUSIONS

Treatment at a high-volume facility is associated with improved long-term patient survival for melanoma. High-volume academic centers have improved patient outcomes compared with other high-volume centers.

Prognostic Value of Lymph Node Yield and Density in Head and Neck Malignancies

Objective

Studies have suggested that the lymph node yield and lymph node density from selective or elective neck dissections are predictive of patient outcomes and may be used for patient counseling, treatment planning, or quality measurement. Our objective was to systematically review the literature and conduct a meta-analysis of studies that investigated the prognostic significance of lymph node yield and/or lymph node density after neck dissection for patients with head and neck cancer.

Data Sources

The Ovid/Medline, Ovid/Embase, and NLM PubMed databases were systematically searched on January 23, 2017, for articles published between January 1, 1946, and January 23, 2017.

Review Methods

We reviewed English-language original research that included survival analysis of patients undergoing neck dissection for a head and neck malignancy stratified by lymph node yield and/or lymph node density. Study data were extracted by 2 independent researchers (S.C. and M.O.). We utilized the DerSimonian and Laird random effects model to account for heterogeneity of studies.

Results

Our search yielded 350 nonduplicate articles, with 23 studies included in the final synthesis. Pooled results demonstrated that increased lymph node yield was associated with a significant improvement in survival (hazard ratio, 0.833; 95% CI, 0.790-0.879). Additionally, we found that increased lymph node density was associated with poorer survival (hazard ratio, 1.916; 95% CI, 1.637-2.241).

Conclusions

Increased nodal yield portends improved outcomes and may be a valuable quality indicator for neck dissections, while increased lymph node density is associated with diminished survival and may be used for postsurgical counseling and planning for adjuvant therapy.

Longitudinal patterns of potentially inappropriate medication use following incident dementia diagnosis

INTRODUCTION

Potentially inappropriate medication (PIM) use in older adults with dementia is an understudied area. We assessed longitudinal changes in PIM exposure by dementia type following dementia diagnosis.

METHODS

We followed 2448 participants aged ≥65 years (52% women, 85.5% Caucasian, mean age 80.9 ± 7.5 years) diagnosed with dementia after enrollment in the National Alzheimer's Coordinating Center (2005-2014). We estimated the association between dementia type and PIM annually for 2 years after diagnosis, using Generalized Estimating Equations.

RESULTS

Participants with Lewy body dementia had more PIM use, and participants with frontotemporal dementia had less PIM use than participants with Alzheimer's disease. In the first year following diagnosis, total number of medications increased, on average, by 10% for Alzheimer's disease and 15% for Lewy body dementia (P < .05 for both).

DISCUSSION

A tailored approach aimed at optimizing drug therapy is needed to mitigate PIM exposure to improve medical care for individuals with dementia.

Asthma-COPD overlap syndrome in the US: a prospective population-based analysis of patient-reported outcomes and health care utilization

Background

Prior work suggests that asthma–COPD overlap syndrome (ACOS) has a greater health burden than asthma alone or COPD alone. In the current study, we have further evaluated the health burden of ACOS in a nationally representative sample of the US population, focusing on patient-reported outcomes and health care utilization and on comparisons with asthma alone and COPD alone. Patient-reported outcomes are especially meaningful, as these include functional activities that are highly valued by patients and are the basis for patient-centered care.

Methods

Using data from the Medical Expenditure Panel Survey (MEPS), we evaluated patient-reported outcomes and health care utilization among participants who were aged 40–85 years and had self-reported, physician-diagnosed asthma or COPD. MEPS administered five rounds of interviews, at baseline and approximately every 6 months over 2.5 years. Patient-reported outcomes included activities of daily living (ADLs), mobility, social/recreational activities, disability days in bed, and health status (Short Form 12, Version 2). Health care utilization included outpatient and emergency department (ED) visits, and hospitalization.

Results

Of 3,486 participants with asthma or COPD, 1,585 (45.4%) had asthma alone, 1,294 (37.1%) had COPD alone, and 607 (17.4%) had ACOS. Relative to asthma alone, ACOS was significantly associated with higher odds of prevalent disability in ADLs and limitations in mobility and social/recreational activities (adjusted odds ratios [adjORs]: 1.91–3.98), as well as with higher odds of incident limitations in mobility and social/recreational activities, disability days in bed, and respiratory-based outpatient and ED visits, and hospitalization (adjORs: 1.86–2.35). In addition, ACOS had significantly worse physical and mental health scores than asthma alone (P-values <0.0001). Relative to COPD alone, ACOS was significantly associated with higher odds of prevalent limitations in mobility and social/recreational activities (adjORs: 1.68–2.06), as well as with higher odds of incident disability days in bed and respiratory-based outpatient and ED visits (adjORs: 1.48–1.74). In addition, ACOS had a significantly worse physical health score, but similar mental health score, as compared with COPD alone (P-values 0.0025 and 0.1578, respectively).

Conclusion

In the US, ACOS is associated with a greater health burden, including patient-reported outcomes and health care utilization, relative to asthma alone and COPD alone.

A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data

BACKGROUND

Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data.

METHODS

We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study.

RESULTS

Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations.

CONCLUSIONS

The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake

Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method.

Evaluation of a two-part regression calibration to adjust for dietary exposure measurement error in the Cox proportional hazards model: A simulation study

Dietary questionnaires are prone to measurement error, which bias the perceived association between dietary intake and risk of disease. Short-term measurements are required to adjust for the bias in the association. For foods that are not consumed daily, the short-term measurements are often characterized by excess zeroes. Via a simulation study, the performance of a two-part calibration model that was developed for a single-replicate study design was assessed by mimicking leafy vegetable intake reports from the multicenter European Prospective Investigation into Cancer and Nutrition (EPIC) study. In part I of the fitted two-part calibration model, a logistic distribution was assumed; in part II, a gamma distribution was assumed. The model was assessed with respect to the magnitude of the correlation between the consumption probability and the consumed amount (hereafter, cross-part correlation), the number and form of covariates in the calibration model, the percentage of zero response values, and the magnitude of the measurement error in the dietary intake. From the simulation study results, transforming the dietary variable in the regression calibration to an appropriate scale was found to be the most important factor for the model performance. Reducing the number of covariates in the model could be beneficial, but was not critical in large-sample studies. The performance was remarkably robust when fitting a one-part rather than a two-part model. The model performance was minimally affected by the cross-part correlation.

Use of two-part regression calibration model to correct for measurement error in episodically consumed foods in a single-replicate study design: EPIC case study

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.