Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims

Diverse analysis approaches have been proposed to distinguish data missing due to death from nonresponse, and to summarize trajectories of longitudinal data truncated by death. We demonstrate how these analysis approaches arise from factorizations of the distribution of longitudinal data and survival information. Models are illustrated using cognitive functioning data for older adults. For unconditional models, deaths do not occur, deaths are independent of the longitudinal response, or the unconditional longitudinal response is averaged over the survival distribution. Unconditional mod- els, such as random effects models fit to unbalanced data, may implicitly impute data beyond the time of death. Fully conditional models stratify the longitudinal response trajectory by time of death. Fully conditional models are effective for describing in- dividual trajectories, in terms of either aging (age, or years from baseline) or dying (years from death). Causal models (principal stratification) as currently applied are fully conditional models, since group differences at one timepoint are described for a cohort that will survive past a later timepoint. Partly conditional models summarize the longitudinal response in the dynamic cohort of survivors. Partly conditional models are serial cross-sectional snapshots of the response, reflecting the average response in survivors at a given timepoint rather than individual trajectories. Joint models of sur- vival and longitudinal response describe the evolving health status of the entire cohort. Researchers using longitudinal data should consider which method of accommodating deaths is consistent with research aims, and use analysis methods accordingly

Trends in Radical Prostatectomy: Centralization, Robotics, and Access to Urologic Cancer Care

Robotic surgery has been widely adopted for radical prostatectomy. We hypothesize that this change is rapidly shifting procedures away from hospitals that do not offer robotics and consequently increasing patient travel

Height, adiposity and body fat distribution and breast density in young women

INTRODUCTION: Breast density is one of the strongest risk factors for breast cancer, but determinants of breast density in young women remain largely unknown. METHOD: Associations of height, adiposity and body fat distribution with percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) were evaluated in a cross-sectional study of 174 healthy women, 25-29 years old. Adiposity and body fat distribution were measured by anthropometry and dual-energy x-ray absorptiometry (DXA), while %DBV and ADBV were measured by magnetic resonance imaging (MRI). Associations were evaluated using linear mixed effects models. All tests of statistical significance are 2-sided. RESULTS: Height was significantly positively associated with %DBV but not ADBV; for each standard deviation (SD) increase in height, %DBV increased by 18.7% in adjusted models. In contrast, all measures of adiposity and body fat distribution were significantly inversely associated with %DBV; a SD increase in body mass index (BMI), percent fat mass, waist circumference and the android:gynoid fat mass ratio (A:G ratio) each was associated significantly with a 44.4% - 47.0% decrease in %DBV after adjustment for childhood BMI and other covariates. Although associations were weaker than for %DBV, all measures of adiposity and body fat distribution also were significantly inversely associated with ADBV before adjustment for childhood BMI. However, after adjustment for childhood BMI only the DXA measures percent fat mass and A:G ratio remained significant; a SD increase in each was associated with a 13.8% - 19.6% decrease in ADBV . In mutually adjusted analysis, percent fat mass and the A:G ratio remained significantly inversely associated with %DBV, but only the A:G ratio was significantly associated with ADBV; a SD increase in A:G ratio was associated with a 18.5% decrease in ADBV. CONCLUSIONS: Total adiposity and body fat distribution are independently inversely associated with %DBV, whereas in mutually adjusted analysis only body fat distribution (A:G ratio) remained significantly inversely associated with ADBV in young women. Research is needed to identify biological mechanisms underlying these associations

The development, usability, and reliability of the Electronic Patient Visit Assessment (ePVA) for head and neck cancer

Background: Annually, over 65,000 persons are diagnosed with head and neck cancer in the United States. During treatment, up to 50% of patients become severely symptomatic with pain, fatigue, mouth sores, and inability to eat. Long term complications are lymphedema, fibrosis, dysphagia, and musculoskeletal impairment. Patients’ ability to perform daily activities and to interact socially may be impaired, resulting in poor quality of life. A pragmatic, clinically useful assessment is needed to ensure early detection and intervention for patients to report symptoms and functional limitations over time. We developed the Electronic Patient Visit Assessment (ePVA) that enables patients to report 42 symptoms related to head and neck cancer and 17 limitations of functional status. This manuscript reports (I) the development of the ePVA, (II) the content validity of the ePVA, and (III) the usability and reliability of the ePVA. Methods: Usability was evaluated using the “Think Aloud” technique to guide the iterative process to refine the ePVA based on participants’ evaluations. After signing the informed consent, 30 participants with head and neck cancer completed the ePVA using digital tablet devices while thinking aloud about ease of use. All patient conversations were recorded and professionally transcribed. Reliability of the ePVA symptom and functional limitation measures was estimated using the Kuder-Richardson test. Convergent validity of the ePVA was evaluated using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 global QoL/health scale. Transcribed qualitative data were analyzed using directed content analysis approach. Quantitative analyses consisted of descriptive statistics and correlation analyses. Results: Among participants, 90% strongly agreed or agreed that the ePVA system was easy to use and 80% were very satisfied. Only minor usability problems were reported due to formatting and software “bugs”. Reporting of usability problems decreased in frequency over the study period and no usability problems were reported by the last 3 participants who completed the ePVA. Based on participants’ suggestions during the iterative process, refinement of the ePVA included increased touch sensitivity of the touch screen technology and customized error messages to improve ease of use. The ePVA also recorded patient reported symptoms (mouth symptoms: 93%, fibrosis: 60%, fatigue: 60%). The ePVA demonstrated acceptable reliability (alpha =0.82–0.85) and convergent validity (ePVA total number of reported symptoms and function limitations was negatively correlated with EORTC QLQ-C30 global QOL/health scale: r=−0.55038, P<0.01). Conclusions: The ePVA was rigorously developed, accepted by patients with satisfaction, and demonstrated acceptable reliability and convergent validity. Future research will use data generated by the ePVA to determine the impact of symptom trajectories on functional status, treatment interruptions and terminations, and health resource use in head and neck cancer

The usefulness of the electronic patient visit assessment (ePVA) as a clinical support tool for real-time interventions in head and neck cancer

Background: Patients with head and neck cancer (HNC) experience painful, debilitating symptoms and functional limitations that can interrupt cancer treatment, and decrease their health-related quality of life (HRQoL). The Electronic Patient Visit Assessment (ePVA) for head and neck is a web-based mHealth patient-reported measure that asks questions about 21 categories of symptoms and functional limitations common to HNC. This article presents the development and usefulness of the ePVA as a clinical support tool for real-time interventions for patient-reported symptoms and functional limitations in HNC. Methods: Between January 2018 and August 2019, 75 participants were enrolled in a clinical usefulness study of the ePVA. Upon signing informed consent, participants completed the ePVA and the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ) general (C30) questionnaire v3.0 (scores range from 0 to 100 with 100 representing best HRQoL). Clinical usefulness of the ePVA was defined as demonstration of reliability, convergent validity with HRQoL, and acceptability of the ePVA (i.e., >70% of eligible participants complete the ePVA at two or more visits and >70% of ePVA reports are read by providers). Formal focus group discussions with the interdisciplinary teamthat cared for patients with HNC guided the development of the ePVA as a clinical support tool. Qualitative and quantitative methods were used throughout the study. Descriptive statistics consisting of means and frequencies, Pearson correlation coefficient, and Student’s t-tests were calculated using SAS 9.4 and STATA. Results: The participants were primarily male (71%), White (76%), diagnosed with oropharyngeal or oralcavity cancers (53%), and undergoing treatment for HNC (69%). Data analyses supported the reliability (alpha =0.85), convergent validity with HRQoL scores, and acceptability of the ePVA. Participants with the highest number of symptoms and functional limitations reported significantly worse HRQoL (sumof symptoms: r=–0.50, P<0.0001; sum of function limitations: r=–0.56, P<0.0001). Ninety-two percent of participants (59 of 64) who had follow-up visits within the 6-month study period completed the ePVA at twoor more visits and providers read 89% (169 of 189) of automated ePVA reports. The use of the ePVA as aclinical support tool for real-time interventions for symptoms and functional limitations reported by patients is described in a clinical exemplar. Conclusions: This research indicates that the ePVA may be a useful mHealth tool as a clinical support tool for real-time interventions for patient-reported symptoms and functional limitations in HNC. The study findings support future translational research to enhance the usefulness of the ePVA in real world settings for early interventions that decrease symptom burden and improve the QoL of patients with HNC

Response to Pearl's Comments on Principal Stratification

Dr. Pearl invites researchers to justify their use of principal stratification. This comment explains how the use of principal stratification simplified a complex mediational problem encountered when evaluating a smoking cessation intervention’s effect on reducing smoking withdrawal symptoms.

Response to Pearl's Comments on Principal Stratification

Dr. Pearl invites researchers to justify their use of principal stratification. This comment explains how the use of principal stratification simplified a complex mediational problem encountered when evaluating a smoking cessation intervention's effect on reducing smoking withdrawal symptoms