Publications

CONTEXT

Although energy conservation strategies are recommended in clinical practice guidelines, little is known about changes in energy levels in oncology patients undergoing cancer treatment.

OBJECTIVES

The objective of this study was to identify variations in the trajectories of morning and evening energy levels and determine which characteristics predicted initial levels and the trajectories of morning and evening energy.

METHODS

Outpatients receiving chemotherapy (CTX) completed demographic and symptom questionnaires six times over two CTX cycles. Energy was assessed using the Lee Fatigue Scale. Hierarchical linear modeling was used to analyze the data.

RESULTS

A large amount of interindividual variability was found in the morning and evening energy trajectories. Patients who lived alone, had childcare responsibilities, had a lower functional status, did not exercise on a regular basis, had lower hemoglobin levels, had lower attentional function, higher trait anxiety, and higher sleep disturbance reported lower morning energy levels at enrollment. Variations in the trajectories of morning energy were associated with a higher body mass index and higher levels of morning energy and higher sleep disturbance scores. For evening energy, patients who were female, white, had lower functional status, and had lower attentional function and higher sleep disturbance reported lower evening energy levels at enrollment. Evening energy levels at enrollment were associated with changes in evening energy over time.

CONCLUSION

Patients undergoing CTX experience decrements in both morning and evening energy. The modifiable characteristics associated with these decrements can be used to design intervention studies to increase energy levels in these patients.

CONTEXT

Evidence suggests that chemotherapy-induced neuropathy (CIN) is a significant problem for cancer survivors. However, a detailed phenotypic characterization of CIN in cancer survivors is not available.

OBJECTIVES

To evaluate between-group differences in demographic and clinical characteristics, as well as in measures of sensation, function, and postural control, in a sample of cancer survivors who received a platinum and/or a taxane-based CTX regimen and did (n = 426) and did not (n = 197) develop CIN.

METHODS

Survivors completed self-report questionnaires and underwent objective testing (i.e., light touch, pain sensation, cold sensation, vibration, muscle strength, grip strength, Purdue Pegboard test, Timed Get Up and Go test, Fullerton Advanced Balance test). Parametric and nonparametric statistics were used to compare between-group differences in study outcomes.

RESULTS

Of the 426 survivors with CIN, 4.9% had CIN only in their upper extremities, 27.0% only in their lower extremities, and 68.1% in both their upper and lower extremities. Demographic and clinical characteristics associated with CIN included the following: older age, lower annual income, higher body mass index, a higher level of comorbidity, being born prematurely, receipt of a higher cumulative dose of chemotherapy, and a poorer functional status. Survivors with CIN had worse outcomes for all of the following objective measures: light touch, pain, temperature, vibration, upper and lower extremity function, and balance.

CONCLUSIONS

This study is the first to provide a detailed phenotypic characterization of CIN in cancer survivors who received a platinum and/or a taxane compound. These data can serve as a benchmark for future studies of CIN in cancer survivors.

BACKGROUND

Novel drug regimens are needed for tuberculosis (TB) treatment. New regimens aim to improve on characteristics such as duration, efficacy, and safety profile, but no single regimen is likely to be ideal in all respects. By linking these regimen characteristics to a novel regimen's ability to reduce TB incidence and mortality, we sought to prioritize regimen characteristics from a population-level perspective.

METHODS AND FINDINGS

We developed a dynamic transmission model of multi-strain TB epidemics in hypothetical populations reflective of the epidemiological situations in India (primary analysis), South Africa, the Philippines, and Brazil. We modeled the introduction of various novel rifampicin-susceptible (RS) or rifampicin-resistant (RR) TB regimens that differed on six characteristics, identified in consultation with a team of global experts: (1) efficacy, (2) duration, (3) ease of adherence, (4) medical contraindications, (5) barrier to resistance, and (6) baseline prevalence of resistance to the novel regimen. We compared scale-up of these regimens to a baseline reflective of continued standard of care. For our primary analysis situated in India, our model generated baseline TB incidence and mortality of 157 (95% uncertainty range [UR]: 113-187) and 16 (95% UR: 9-23) per 100,000 per year at the time of novel regimen introduction and RR TB incidence and mortality of 6 (95% UR: 4-10) and 0.6 (95% UR: 0.3-1.1) per 100,000 per year. An optimal RS TB regimen was projected to reduce 10-y TB incidence and mortality in the India-like scenario by 12% (95% UR: 6%-20%) and 11% (95% UR: 6%-20%), respectively, compared to current-care projections. An optimal RR TB regimen reduced RR TB incidence by an estimated 32% (95% UR: 18%-46%) and RR TB mortality by 30% (95% UR: 18%-44%). Efficacy was the greatest determinant of impact; compared to a novel regimen meeting all minimal targets only, increasing RS TB treatment efficacy from 94% to 99% reduced TB mortality by 6% (95% UR: 1%-13%, half the impact of a fully optimized regimen), and increasing the efficacy against RR TB from 76% to 94% lowered RR TB mortality by 13% (95% UR: 6%-23%). Reducing treatment duration or improving ease of adherence had smaller but still substantial impact: shortening RS TB treatment duration from 6 to 2 mo lowered TB mortality by 3% (95% UR: 1%-6%), and shortening RR TB treatment from 20 to 6 mo reduced RR TB mortality by 8% (95% UR: 4%-13%), while reducing nonadherence to the corresponding regimens by 50% reduced TB and RR TB mortality by 2% (95% UR: 1%-4%) and 6% (95% UR: 3%-10%), respectively. Limitations include sparse data on key model parameters and necessary simplifications to model structure and outcomes.

CONCLUSIONS

In designing clinical trials of novel TB regimens, investigators should consider that even small changes in treatment efficacy may have considerable impact on TB-related incidence and mortality. Other regimen improvements may still have important benefits for resource allocation and outcomes such as patient quality of life.

Under the U.S. Lung Allocation Score (LAS) system, older and sicker patients are prioritized for lung transplantation (LT). The impact of these changes on health-related quality of life (HRQL) after transplant has not been determined. In a single-center prospective cohort study from 2010 to 2016, we assessed HRQL before and repeatedly after LT for up to 3 years using the SF12-Physical and Mental Health, the respiratory-specific Airway Questionnaire 20-Revised, and the Euroqol 5D/Visual Analog Scale utility measures by multivariate linear mixed models jointly modeled with death. We also tested changes in LT-Valued Life Activities disability, BMI, allograft function, and 6-min walk test exercise capacity as predictors of HRQL change. Among 211 initial participants (92% of those eligible), LT improved HRQL by all 5 measures (p < 0.05) and all but SF12-Mental Health improved by threefold or greater than the minimally clinically important difference. Compared to younger participants, those aged ≥65 improved less in SF12-Physical and Mental Health (p < 0.01). Improvements in disability accounted for much of the HRQL improvement. In the LAS era, LT affords meaningful and durable HRQL improvements, mediated by amelioration of disability. Identifying factors limiting HRQL improvement in selected subgroups, especially those aged ≥65, are needed to maximize the net benefits of LT.

BACKGROUND

Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data.

RESULTS

We demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with -located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data.

CONCLUSIONS

EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.

Populations are often divided categorically into distinct racial/ethnic groups based on social rather than biological constructs. Genetic ancestry has been suggested as an alternative to this categorization. Herein, we typed over 450,000 CpG sites in whole blood of 573 individuals of diverse Hispanic origin who also had high-density genotype data. We found that both self-identified ethnicity and genetically determined ancestry were each significantly associated with methylation levels at 916 and 194 CpGs, respectively, and that shared genomic ancestry accounted for a median of 75.7% (IQR 45.8% to 92%) of the variance in methylation associated with ethnicity. There was a significant enrichment (p=4.2×10) of ethnicity-associated sites amongst loci previously associated environmental exposures, particularly maternal smoking during pregnancy. We conclude that differential methylation between ethnic groups is partially explained by the shared genetic ancestry but that environmental factors not captured by ancestry significantly contribute to variation in methylation.