A Health-Related Quality of Life Measure for Patients Who Undergo Minimally Invasive Glaucoma Surgery.

PURPOSE: To develop a standardized patient-reported outcome measure to assess the impact of glaucoma and treatment, including minimally invasive glaucoma surgery (MIGS), on health-related quality of life (HRQOL). DESIGN: Observational study before and after concomitant cataract and FDA-approved implantable MIGS device surgery to provide information on the measure's performance in assessing HRQOL. METHODS SETTING: Survey administration was done by electronic patient-reported outcomes (ePRO) application to patients at multiple sites on a computer, iPad, or similar device. PATIENT POPULATION: One hundred eighty-four adults completed a baseline survey, 124 completed a survey 3 months after surgery, and 106 completed the 1-month test-retest reliability survey. The age range was 37-89, and the average age was 72. Most of the respondents were female (57%), non-Hispanic White (81%), and had a college degree (56%). MAIN OUTCOME MEASURES: The Glaucoma Outcomes Survey (GOS) includes 42 questions assessing functional limitations (27 items), vision-related symptoms (7 items), psychosocial issues (7 items) and satisfaction with microinvasive glaucoma surgery (1 item). The three multiple-item scales were scored on a 0-100 range, with a higher score indicating worse health. RESULTS: Internal consistency reliability estimates ranged from 0.75 (vision-related symptoms) to 0.93 (functional limitations) and one-month test-retest intraclass correlations ranged from 0.65 (PROMIS global mental health) to 0.92 (functional limitations). Product-moment correlations among the GOS scales ranged from 0.56 to 0.60. Improvement in visual acuity in the study eye from baseline to the 3-month follow-up was significantly related to improvements in GOS functional limitations (r =0.18, p =0.0485), vision-related symptoms (r = 0.19, p = 0.0386), and psychosocial concerns (r = 0.18, p =0.0503). The highest proportion of responders to treatment was seen for the GOS functional limitations scale (48%), followed by GOS psychosocial issues (21%) and GOS vision-related symptoms (17%). CONCLUSIONS: This study provides initial support for using the GOS instrument in ophthalmic procedures such as MIGS. Further evaluation of the GOS in other samples, including different patient subgroups and clinical settings, will be valuable. The instrument may be useful for evaluations of other treatments for glaucoma.

The PROMIS-16 reproduces the PROMIS-29 physical and mental health summary scores accurately in a probability-based internet panel.

PURPOSE: The Patient-Reported Outcomes Measurement Information System® (PROMIS)-16 assesses the same multi-item domains but does not include the pain intensity item in the PROMIS-29. We evaluate how well physical and mental health summary scores estimated from the PROMIS-16 reproduce those estimated using the PROMIS-29. METHODS: An evaluation of data collected from 4130 respondents from the KnowledgePanel. Analyses include confirmatory factor analysis to assess physical and mental health latent variables based on PROMIS-16 scores, reliability estimates for the PROMIS measures, mean differences and correlations of scores estimated by the PROMIS-16 with those estimated by the PROMIS-29, and associations between differences in corresponding PROMIS-16 and PROMIS-29 scores by sociodemographic characteristics. RESULTS: A two-factor (physical and mental health) model adequately fits the PROMIS-16 scores. Reliability estimates for the PROMIS-16 measures were slightly lower than for the PROMIS-29 measures. There were minimal differences between PROMIS physical and mental health summary scores estimated using the PROMIS-16 or the PROMIS-29. PROMIS-16 and PROMIS-29 score differences by sociodemographic characteristics were small. Using the PROMIS pain intensity item when scoring the PROMIS-16 produced similar estimates of physical and mental health summary scores. CONCLUSION: The PROMIS-16 provides similar estimates of the PROMIS-29 physical and mental health summary scores. The high reliability of these scores indicates they are accurate enough for use with individual patients.

Is Primary Care Patient Experience Associated with Provider-Patient Language Concordance and Use of Interpreters for Spanish-preferring Patients: A Systematic Literature Review.

BACKGROUND: Healthcare provided by a bilingual provider or with the assistance of an interpreter improves care quality; however, their associations with patient experience are unknown. We reviewed associations of patient experience with provider-patient language concordance (LC) and use of interpreters for Spanish-preferring patients. METHOD: We reviewed articles from academic databases 2005-2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and Joanna Briggs Institute Checklists to rate study quality. We reviewed 217 (of 2193) articles, yielding 17 for inclusion. RESULTS: Of the 17 included articles, most articles focused on primary (n = 6 studies) or pediatric care (n = 5). All were cross-sectional, collecting data by self-administered surveys (n = 7) or interviews (n = 4). Most assessed the relationship between LC or interpreter use and patient experience by cross-sectional associations (n = 13). Two compared subgroups, and two provided descriptive insights into the conversational content (provider-interpreter-patient). None evaluated interventions, so evidence on effective strategies is lacking. LC for Spanish-preferring patients was a mix of null findings (n = 4) and associations with better patient experience (n = 3) (e.g., receiving diet/exercise counseling and better provider communication). Evidence on interpreter use indicated better (n = 2), worse (n = 2), and no association (n = 2) with patient experience. Associations between Spanish-language preference and patient experience were not significant (n = 5) or indicated worse experience (n = 4) (e.g., long waits, problems getting appointments, and not understanding nurses). CONCLUSION: LC is associated with better patient experience. Using interpreters is associated with better patient experience but only with high-quality interpreters. Strategies are needed to eliminate disparities and enhance communication for all Spanish-preferring primary care patients, whether with a bilingual provider or an interpreter.

Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods.

OBJECTIVES: Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. METHODS: This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. RESULTS: We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. CONCLUSIONS: The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Narrative comments about pediatric inpatient experiences yield substantial information beyond answers to closed-ended CAHPS survey questions.

PURPOSE: Adults' comments on patient experience surveys explain variation in provider ratings, with negative comments providing more actionable information than positive comments. We investigate if narrative comments on the Consumer Assessment of Healthcare Providers and Systems (CAHPS®) survey of inpatient pediatric care (Child HCAHPS) account for global perceptions of the hospital beyond that explained by reports about specific aspects of care. METHODS: We analyzed 545 comments from 927 Child HCAHPS surveys completed by parents and guardians of hospitalized children with at least a 24-h hospital stay from July 2017 to December 2020 at an urban children's hospital. Comments were coded for valence (positive/negative/mixed) and actionability and used to predict Overall Hospital Rating and Willingness to Recommend the Hospital along with Child HCAHPS composite scores. RESULTS: Comments were provided more often by White and more educated respondents. Negative comments and greater actionability of comments were significantly associated with Child HCAHPS global rating measures, controlling for responses to closed-ended questions, and child and respondent characteristics. Each explained an additional 8% of the variance in respondents' overall hospital ratings and an additional 5% in their willingness to recommend the hospital. CONCLUSIONS: Child HCAHPS narrative comment data provide significant additional information about what is important to parents and guardians during inpatient pediatric care beyond closed-ended composites. PRACTICE IMPLICATIONS: Quality improvement efforts should include a review of narrative comments alongside closed-ended responses to help identify ways to improve inpatient care experiences. To promote health equity, comments should be encouraged for racial-and-ethnic minority patients and those with less educational attainment.

Development of an ultra-short measure of eight domains of health-related quality of life for research and clinical care: the patient-reported outcomes measurement information system® PROMIS®-16 profile.

PURPOSE: We describe development of a short health-related quality of life measure, the patient-reported outcomes measurement information system® (PROMIS®)-16 Profile, which generates domain-specific scores for physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function, and fatigue. METHODS: An empirical evaluation of 50 candidate PROMIS items and item pairs was conducted using data from a sample of 5775 respondents from Amazon's Mechanical Turk (MTurk). Results and item response theory information curves for a subset of item pairs were presented and discussed in a stakeholder meeting to narrow the candidate item sets. A survey of the stakeholders and 124 MTurk adults was conducted to solicit preferences among remaining candidate items and finalize the measure. RESULTS: Empirical evaluation showed minimal differences in basic descriptive statistics (e.g., means, correlations) and associations with the PROMIS-29 + 2 Profile, thus item pairs were further considered primarily based on item properties and content. Stakeholders discussed and identified subsets of candidate item pairs for six domains, and final item pairs were agreed upon for two domains. Final items were selected based on stakeholder and MTurk-respondent preferences. The PROMIS-16 profile generates eight domain scores with strong psychometric properties. CONCLUSION: The PROMIS-16 Profile provides an attractive brief measure of eight distinct domains of health-related quality of life, representing an ideal screening tool for clinical care, which can help clinicians quickly identify distinct areas of concern that may require further assessment and follow-up. Further research is needed to confirm and extend these findings.

Associations of Primary Care Provider Burnout with Quality Improvement, Patient Experience Measurement, Clinic Culture, and Job Satisfaction.

BACKGROUND: Burnout among providers negatively impacts patient care experiences and safety. Providers at Federally Qualified Health Centers (FQHC) are at high risk for burnout due to high patient volumes; inadequate staffing; and balancing the demands of patients, families, and team members. OBJECTIVE: Examine associations of provider burnout with their perspectives on quality improvement (QI), patient experience measurement, clinic culture, and job satisfaction. DESIGN: We conducted a cross-sectional provider survey about their perspectives including the single-item burnout measure. We fit separate regression models, controlling for provider type, gender, being multilingual, and fixed effects for clinic predicting outcome measures from burnout. PARTICIPANTS: Seventy-four providers from 44 clinics in large, urban FQHC (52% response rate; n = 174). MAIN MEASURES: Survey included a single-item, self-defined burnout measure adapted from the Physician Worklife Survey, and measures from the RAND AMA Study survey, Heath Tracking Physician survey, TransforMed Clinician and Staff Questionnaire, Physician Worklife Survey, Minimizing Errors Maximizing Outcomes survey, and surveys by Friedberg et al. 31 and Walling et al. 32 RESULTS: Thirty percent of providers reported burnout. Providers in clinics with more facilitative leadership reported not being burned out (compared to those reporting burnout; p-values < 0.05). More pressures related to patient care and lower job satisfaction were associated with burnout (p-values < 0.05). CONCLUSIONS: Creating provider-team relationships and environments where providers have the time and space necessary to discuss changes to improve care, ideas are shared, leadership supports QI, and QI is monitored and discussed were related to not being burned out. Reducing time pressures and improving support needed for providers to address the high-need levels of FQHC patients can also decrease burnout. Such leadership and support to improving care may be a separate protective factor against burnout. Research is needed to further examine which aspects of leadership drive down burnout and increase provider involvement in change efforts and improving care.

Mapping of the PROMIS global health measure to the PROPr in the United States.

BACKGROUND: The Patient-Reported Outcomes Measurement and Information System (PROMIS®) global health items (global-10) yield physical and mental health scale scores and the PROMIS-Preference (PROPr) scoring system estimated from PROMIS domain scores (e.g., PROMIS-29 + 2) produces a single score anchored by 0 (dead or as bad as being dead) to 1 (full health). A link between the PROMIS global-10 and the PROPr is needed. METHODS: The PROMIS-29 + 2 and the PROMIS global-10 were administered to 4102 adults in the Ipsos KnowledgePanel in 2022. The median age was 52 (range 18-94), 50% were female, 70% were non-Hispanic White, and 64% were married or living with a partner. The highest level of education completed for 26% of the sample was a high school degree or general education diploma and 44% worked full-time. We estimated correlations of the PROPr with the PROMIS global health items and the global physical and mental health scales. We examined the adjusted R2 and estimated correlations between predicted and observed PROPr scores. RESULTS: Product-moment correlations between the PROMIS global health items and the PROPr ranged from 0.50 to 0.63. The PROMIS global physical health and mental health scale scores correlated 0.74 and 0.60, respectively, with the PROPr. The adjusted R2 in the regression of the PROPr on the PROMIS global health items was 64%. The equated PROPr preference scores correlated (product-moment) 0.80 (n = 4043; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation (two-way random effects model) was 0.80. The normalized mean absolute error (NMAE) was 0.45 (SD = 0.43). The adjusted R2 in the OLS regression of the PROPr on the PROMIS global health scales was 59%. The equated PROPr preference scores correlated (product-moment) was 0.77 (n = 4046; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation was 0.77. The NMAE was 0.49 (SD = 0.45). CONCLUSIONS: Regression equations provide a reasonably accurate estimate of the PROPr preference-based score from the PROMIS global health items or scales for group-level comparisons. These estimates facilitate cost-effectiveness research and meta-analyses. The estimated PROPr scores are not accurate enough for individual-level applications. Future evaluations of the prediction equations are needed.

How Well Do Seven Self-Report Measures Represent Underlying Back Pain Impact?

BACKGROUND: The extent to which different measures of back pain impact represent an underlying common factor has implications for decisions about which one to use in studies of pain management and estimating one score from others. AIMS: To determine if different self-report back pain impact measures represent an underlying pain latent variable and estimate associations with it. METHOD: Seven pain impact measures completed by Amazon Mechanical Turk adults are used to estimate internal consistency reliability and associations: Oswestry Disability Index (ODI), Roland-Morris Disability Questionnaire (RMDQ), short form of the Örebro Musculoskeletal Pain Questionnaire (OMPQ), Subgroups for Targeted Treatment (STarT) Back Tool, the Graded Chronic Pain Scale (GCPS) disability score, PEG (Pain intensity, interference with Enjoyment of life, interference with General activity), and Impact Stratification Score (ISS). RESULTS: The sample of 1,874 adults with back pain had an average age of 41 and 52% were female. Sixteen percent were Hispanic, 7% non-Hispanic Black, 5% non-Hispanic Asian, and 71% non-Hispanic White. Internal consistency reliability estimates ranged from 0.710 (OMPQ) to 0.923 (GCPS). Correlations among the measures ranged from 0.609 (RMDQ with OMPQ) to 0.812 (PEG with GCPS). Standardized factor loadings on the pain latent variable ranged from 0.782 (RMDQ) to 0.870 (ISS). CONCLUSIONS: Scores of each measure can be estimated from the others for use in research.

Predictors of Pain Management Strategies in Adults with Low-Back Pain: A Secondary Analysis of Amazon Mechanical Turk Survey Data.

Objective: To evaluate the associations between baseline demographics, health conditions, pain management strategies, and health-related quality-of-life (HRQoL) measures with pain management strategies at 3-month follow-up in respondents reporting current low-back pain (LBP). Study design: Cohort study of survey data collected from adults with LBP sampled from Amazon Mechanical Turk crowdsourcing panel. Methods: Demographics, health conditions, and the Patient-Reported Outcomes Measurement Information System (PROMIS)-10 were included in the baseline survey. Respondents reporting LBP completed a more comprehensive survey inquiring about pain management strategies and several HRQoL measures. Bivariate then multivariate logistic regression estimated odds ratios (ORs) with 95% confidence intervals (CIs) for the association between baseline characteristics and pain management utilization at 3-month follow-up. Model fit statistics were evaluated to assess the predictive value. Results: The final cohort included 717 respondents with completed surveys. The most prevalent pain management strategy at follow-up was other care (n = 474), followed by no care (n = 94), conservative care only (n = 76), medical care only (n = 51), and medical and conservative care combined (n = 22). The conservative care only group had higher (better) mental and physical health PROMIS-10 scores as opposed to the medical care only and combination care groups, which had lower (worse) physical health scores. In multivariate models, estimated ORs (95% CIs) for the association between baseline and follow-up pain management ranged from 4.6 (2.7-7.8) for conservative care only to 16.8 (6.9-40.7) for medical care only. Additional significant baseline predictors included age, income, education, workman's compensation claim, Oswestry Disability Index score, and Global Chronic Pain Scale grade. Conclusions: This study provides important information regarding the association between patient characteristics, HRQoL measures, and LBP-related pain management utilization.

Performance of the Physical Functioning Activities of Daily Living Scale in the 2020 Medicare Health Outcomes Survey.

OBJECTIVE: Assessing functional limitations for adults at high risk of frailty yields valuable information for identifying those in need of therapy. We evaluate a self-report measure used to assess physical function among Medicare recipients in the United States. DESIGN: Secondary analysis of the 2020 Medicare Health Outcomes Survey. SETTING: A random sample of adult enrollees of 510 managed care plans. PARTICIPANTS: 287,476 adults (37% completion rate): 58% women; 16% were <65 years old (entitled via disability), 50% 65-74, and 34% 75 or older; 77% White, 14% Black, and 8% another race; 19% had

Comparison of patient-reported outcomes measurement information system (PROMIS®)-29 and PROMIS global physical and mental health scores.

PURPOSE: The Patient-Reported Outcomes Measurement and Information System (PROMIS®): includes the PROMIS-29 physical and mental health summary and the PROMIS global physical and mental health scores. It is unknown how these scores coincide with one another. This study examines whether the scores yield similar or different information. METHODS: The PROMIS-29 and the PROMIS global health items were administered to 5804 adults from Amazon's Mechanical Turk (MTurk) in 2021-2022 and to 4060 adults in the Ipsos KnowledgePanel (KP) in 2022. RESULTS: The median age of those in MTurk (KP) was 36 (54) and 53% (50%) were male. Mean T-scores on the PROMIS-29 and PROMIS global physical health scales were similar, but PROMIS global mental health was 3-4 points lower than the PROMIS-29 mental health summary score. Product-moment correlations ranged from 0.69 to 0.81 between the PROMIS-29 physical health and PROMIS global physical health scales and 0.56-0.69 between the mental health scales. Multi-trait multimethod analyses indicated that only a small proportion of the correlations between the two methods of measuring mental health were significantly more highly correlated with one another than correlations between physical and mental health. CONCLUSIONS: PROMIS-29 and PROMIS global mental health scales provide different information and, therefore, study conclusions may vary depending on which measure is used. Interpretation of results needs to consider that the PROMIS-29 mental health scale is a weighted combination of specific domains while the PROMIS global mental health scale is based on general mental health perceptions. Further comparisons of methods of assessing mental health are needed.

Estimating individual health-related quality of life changes in low back pain patients.

BACKGROUND: There is a need to evaluate different options for estimating individual change in health-related quality of life for patients with low back pain. METHODS: Secondary analysis of data collected at baseline and 6 weeks later in a randomized trial of 749 adults with low back pain receiving usual medical care (UMC) or UMC plus chiropractic care at a small hospital at a military training site or two large military medical centers. The mean age was 31; 76% were male and 67% were White. The study participants completed the Patient-Reported Outcomes Measurement Information System (PROMIS®)-29 v 1.0 physical function, pain interference, pain intensity, fatigue, sleep disturbance, depression, anxiety, satisfaction with participation in social roles, physical summary, and mental health summary scores (T-scored with mean = 50 and standard deviation (SD) = 10 in the U.S. general population). RESULTS: Reliability estimates at the baseline ranged from 0.700 to 0.969. Six-week test-retest intraclass correlation estimates were substantially lower than these estimates: the median test-retest intraclass correlation for the two-way mixed-effects model was 0. 532. Restricting the test-retest reliability estimates to the subset who reported they were about the same as at baseline on a retrospective rating of change item increased the median test-retest reliability to 0.686. The amount of individual change that was statistically significant varied by how reliability was estimated, and which SD was used. The smallest change needed was found when internal consistency reliability and the SD at baseline were used. When these values were used, the amount of change needed to be statistically significant (p < .05) at the individual level ranged from 3.33 (mental health summary scale) to 12.30 (pain intensity item) T-score points. CONCLUSIONS: We recommend that in research studies estimates of the magnitude of individual change needed for statistical significance be provided for multiple reliability and standard deviation estimates. Whenever possible, patients should be classified based on whether they 1) improved significantly and perceived they got better, 2) improved significantly but did not perceive they were better, 3) did not improve significantly but felt they got better, or 4) did not improve significantly or report getting better.

Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample.

BACKGROUND: In 2014, the National Institute of Health Pain Consortium's research task force (RTF) on research standards for chronic low back pain (CLBP) proposed the Impact Stratification Score (ISS) as a patient-reported outcome measure that could stratify patients by the impact CLBP has on their lives. This work compares three newly developed ISS-based classifications to the RTF's original to provide an optimal recommendation. METHODS: The online sample included 1226 individuals from Amazon's Mechanical Turk who indicated having non-specific CLBP, average age of 40, 49% female, and 67% White. Participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items as well the Roland-Morris Disability Questionnaire (RMDQ) and Graded Chronic Pain Scale (GCPS). Other items included high-impact chronic pain; not working due to health problems; overall health; and number of healthcare visits for back pain in the past 6 months. Three new classifications were created using quartiles (Classification 2), latent profile analysis (Classification 3), and one modeled after the GCPS (Classification 4). Classifications were subsequently compared to the RTF-proposed classification (Classification 1) on several concurrent and prognostic criteria. RESULTS: Classification 1 had three CLBP severity groups, four in Classification 2, three in Classification 3, and four in Classification 4. All novel classifications improved upon the original. Classification 2 performed best at minimizing the classification of those with negative outcomes into the lowest severity groups at baseline (e.g., 11% with RMDQ ≥ 7) and 6 months (e.g., 8.2% had fair/poor health). Classification 4 performed best at maximizing classification of those with negative outcomes into the most severe group concurrently (e.g., 100% had GCPS grade ≥ 2) and at 6 months (e.g., 100% with RMDQ ≥ 7). CONCLUSIONS: We developed three ISS-based classification schemes and tested them against several outcomes. All three improved upon the original scheme. While appearing more optimal than other classifications in the lowest severity groups, Classification 2 presents some considerations and limitations. Given that Classification 4 was an improvement at the lowest end of severity and was the best at the highest end, it is our tentative recommendation that this approach be adopted to classify individuals with non-specific CLBP.

Health-related quality of life in a systematically assessed cohort of children and adults with urea cycle disorders.

PURPOSE: Individuals with urea cycle disorders (UCDs) may develop recurrent hyperammonemia, episodic encephalopathy, and neurological sequelae which can impact Health-related Quality of Life (HRQoL). To date, there have been no systematic studies of HRQoL in people with UCDs. METHODS: We reviewed HRQoL and clinical data for 190 children and 203 adults enrolled in a multicenter UCD natural history study. Physical and psychosocial HRQoL in people with UCDs were compared to HRQoL in healthy people and people with phenylketonuria (PKU) and diabetes mellitus. We assessed relationships between HRQoL, UCD diagnosis, and disease severity. Finally, we calculated sample sizes required to detect changes in these HRQoL measures. RESULTS: Individuals with UCDs demonstrated worse physical and psychosocial HRQoL than their healthy peers and peers with PKU and diabetes. In children, HRQoL scores did not differ by diagnosis or severity. In adults, individuals with decreased severity had worse psychosocial HRQoL. Finally, we show that a large number of individuals would be required in clinical trials to detect differences in HRQoL in UCDs. CONCLUSION: Individuals with UCDs have worse HRQoL compared to healthy individuals and those with PKU and diabetes. Future work should focus on the impact of liver transplantation and other clinical variables on HRQoL in UCDs.

Dynamic Risk Prediction of Treatment Discontinuation Using Patient-Reported Outcomes Data in the Phase III NSABP B-35 Trial.

Predicting an individual's risk of treatment discontinuation is critical for the implementation of precision chemoprevention. We developed partly conditional survival models to predict discontinuation of tamoxifen or anastrozole using patient-reported outcome (PRO) data from postmenopausal women with ductal carcinoma in situ enrolled in the NSABP B-35 clinical trial. In a secondary analysis of the NSABP B-35 clinical trial PRO data, we proposed two models for treatment discontinuation within each treatment arm (anastrozole or tamoxifen treated patients) using partly conditional Cox-type models with time-dependent covariates. A 70/30 split of the sample was used for the training and validation datasets. The predictive performance of the models was evaluated using calibration and discrimination measures based on the Brier score and AUC from time-dependent ROC curves. The predictive models stratified high-risk versus low-risk early discontinuation at a 6-month horizon. For anastrozole-treated patients, predictive factors included baseline body mass index (BMI) and longitudinal patient-reported symptoms such as insomnia, joint pain, hot flashes, headaches, gynecologic symptoms, and vaginal discharge, all collected up to 12 months [Brier score, 0.039; AUC, 0.76; 95% confidence interval (CI), 0.57-0.95]. As for tamoxifen-treated patients, predictive factors included baseline BMI, and time-dependent covariates: cognitive problems, feelings of happiness, calmness, weight problems, and pain (Brier score, 0.032; AUC, 0.78; 95% CI, 0.65-0.91). A real-time calculator based on these models was developed in Shiny to create a web-based application with a future goal to aid healthcare professionals in decision-making. PREVENTION RELEVANCE: The dynamic prediction provided by partly conditional models offers valuable insights into the treatment discontinuation risks using PRO data collected over time from clinical trial participants. This tool may benefit healthcare professionals in identifying patients at high risk of premature treatment discontinuation and support interventions to prevent potential discontinuation.

Embedding research study recruitment within the patient portal preCheck-in.

OBJECTIVE: Patient portals are increasingly used to recruit patients in research studies, but communication response rates remain low without tactics such as financial incentives or manual outreach. We evaluated a new method of study enrollment by embedding a study information sheet and HIPAA authorization form (HAF) into the patient portal preCheck-in (where patients report basic information like allergies). MATERIALS AND METHODS: Eligible patients who enrolled received an after-visit patient-reported outcomes survey through the patient portal. No additional recruitment/messaging efforts were made. RESULTS: A total of 386 of 843 patients completed preCheck-in, 308 of whom signed the HAF and enrolled in the study (37% enrollment rate). Of 93 patients who were eligible to receive the after-visit survey, 45 completed it (48% completion rate). CONCLUSION: Enrollment and survey completion rates were higher than what is typically seen with recruitment by patient portal messaging, suggesting that preCheck-in recruitment can enhance research study recruitment and warrants further investigation.

Effects of Excluding Those Who Report Having "Syndomitis" or "Chekalism" on Data Quality: Longitudinal Health Survey of a Sample From Amazon's Mechanical Turk.

BACKGROUND: Researchers have implemented multiple approaches to increase data quality from existing web-based panels such as Amazon's Mechanical Turk (MTurk). OBJECTIVE: This study extends prior work by examining improvements in data quality and effects on mean estimates of health status by excluding respondents who endorse 1 or both of 2 fake health conditions ("Syndomitis" and "Chekalism"). METHODS: Survey data were collected in 2021 at baseline and 3 months later from MTurk study participants, aged 18 years or older, with an internet protocol address in the United States, and who had completed a minimum of 500 previous MTurk "human intelligence tasks." We included questions about demographic characteristics, health conditions (including the 2 fake conditions), and the Patient Reported Outcomes Measurement Information System (PROMIS)-29+2 (version 2.1) preference-based score survey. The 3-month follow-up survey was only administered to those who reported having back pain and did not endorse a fake condition at baseline. RESULTS: In total, 15% (996/6832) of the sample endorsed at least 1 of the 2 fake conditions at baseline. Those who endorsed a fake condition at baseline were more likely to identify as male, non-White, younger, report more health conditions, and take longer to complete the survey than those who did not endorse a fake condition. They also had substantially lower internal consistency reliability on the PROMIS-29+2 scales than those who did not endorse a fake condition: physical function (0.69 vs 0.89), pain interference (0.80 vs 0.94), fatigue (0.80 vs 0.92), depression (0.78 vs 0.92), anxiety (0.78 vs 0.90), sleep disturbance (-0.27 vs 0.84), ability to participate in social roles and activities (0.77 vs 0.92), and cognitive function (0.65 vs 0.77). The lack of reliability of the sleep disturbance scale for those endorsing a fake condition was because it includes both positively and negatively worded items. Those who reported a fake condition reported significantly worse self-reported health scores (except for sleep disturbance) than those who did not endorse a fake condition. Excluding those who endorsed a fake condition improved the overall mean PROMIS-29+2 (version 2.1) T-scores by 1-2 points and the PROMIS preference-based score by 0.04. Although they did not endorse a fake condition at baseline, 6% (n=59) of them endorsed at least 1 of them on the 3-month survey and they had lower PROMIS-29+2 score internal consistency reliability and worse mean scores on the 3-month survey than those who did not report having a fake condition. Based on these results, we estimate that 25% (1708/6832) of the MTurk respondents provided careless or dishonest responses. CONCLUSIONS: This study provides evidence that asking about fake health conditions can help to screen out respondents who may be dishonest or careless. We recommend this approach be used routinely in samples of members of MTurk.