Evaluating the agreement between different substance use recall periods in multiple HIV cohorts.

BACKGROUND: This study aims to evaluate the agreement in substance use on both binary and ordinal scales between 3-month and 6-month recall periods with samples from different communities, demographic backgrounds, and HIV status. METHODS: We administered the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) to 799 participants from three different North American cohorts focused on substance use and HIV. We conducted a within-person agreement analysis by calculating the agreement levels and Kappa statistic between data collected using the 3-month recall ASSIST and 6-month custom substance use surveys as well as different terminology for each substance in multiple cohorts. RESULTS: For all drugs studied, the agreement on the binary use or ordinal frequency of use metrics showed a high agreement level between 80.4% and 97.9% and an adequate adjusted kappa value between 0.61 and 0.96, suggesting substantial agreement. According to the agreement criteria we proposed, substance use data collected using different recall periods and with variation in drug names can be harmonized across cohorts. CONCLUSIONS: This study is the first to evaluate the feasibility of data harmonization of substance use by demonstrating high level of agreement between different recall periods in different cohorts. The results can inform data harmonization efforts in consortia where data are collected from cohorts using different questions and recall periods.

Linking the KOOS-PS to PROMIS Physical Function in Knee Patients Evaluated for Surgery.

INTRODUCTION: The Knee Injury and Osteoarthritis Outcome Score-Physical Function Short-form and the Patient-Reported Outcomes Measurement Information System Physical Function are widely used patient-reported outcome measures in orthopaedic practice and research. It would be helpful for clinicians and researchers to compare scores obtained on one instrument with those collected on another. To achieve this goal, this study conducted a linking analysis and computed a crosswalk table between these two scales. DATA: The data of this study were collected as part of the clinical care of total knee arthroplasty patients in a large urban and suburban health system. The sample was a mix of responses from nonsurgical (no surgery performed), preoperative (before surgical intervention), and postoperative (after surgical intervention) groups. METHODS: This study applied five linking methods: the item response theory (IRT)-based linking methods including fixed-parameter calibration, separate-parameter calibration with Stocking-Lord constants, and calibrated projection; and the equipercentile methods with log-linear smoothing and nonsmoothing approaches. Before conducting the linking analysis, we checked the linking assumptions including the similar content of the two scales, the unidimensionality of the combined scales, and the population invariance. The results of the five linking methods were evaluated by mean difference, SD, root-mean-squared deviation, intraclass correlation coefficient of the observed T scores and the crosswalk-derived T scores. RESULTS: The linking assumptions were all met. T scores generated from the Stocking-Lord crosswalk had the smallest mean difference (= -0.03) and relatively small SD (= 4.91) and root-mean-squared deviation (= 4.91) among the five linking methods. We validated this crosswalk in a larger sample with the nonsurgical, preoperative, and postoperative groups and in an external sample. DISCUSSION: This study provides clinicians and researchers a practical tool (ie, a crosswalk table) to link scores from two popular physical function measures. Given the diversity of patient-reported outcome measures in use for knee conditions, these crosswalk tables would accelerate clinical and research interpretation of aggregating functional outcomes among the patients evaluated for knee surgery each year.

Do You Recall?: Results From a Within-Person Recall Study of the Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form v2.0 - Physical Function 8c.

OBJECTIVES: This study aimed to determine whether responses to Patient-Reported Outcomes Measurement Information System Short Form v2.0 - Physical Function 8c (PROMIS PF8c) items differed when the use of a 7-day recall period was compared with no specified recall period. METHODS: Using a within-subject design, we surveyed 1810 individuals from the US general population, administering PROMIS PF8c at survey beginning and end. The order of measure presentation was randomly assigned. We calculated recall difference scores (RDSs) as no recall score minus 7-day recall score using both item response theory-based T scores and raw summed scores. We examined the distribution and created Bland-Altman plots for both RDSTscore and RDSRaw. We also calculated correlations between no recall versus 7-day recall T score and raw scores. Finally, we determined whether differences in no recall versus 7-day recall scores were associated with patient-reported PF. RESULTS: RDSTscore and RDSRaw had means (root mean square differences) of 0.00 (5.43) and -0.04 (3.79), respectively. The vast majority (%) of RDSTscore and RDSRaw values fell between the Bland-Altman limits of agreement (-10.65 to 10.66 and -7.46 to 7.38, respectively). Pearson's correlations between no recall and 7-day recall for T scores and raw scores were 0.88 and 0.87, respectively. Effect sizes for mean RDSTscore and RDSRaw compared across level of Eastern Oncology Cooperative Group performance status, patient global impression of PF severity, and single PF items were near 0. CONCLUSIONS: We did not find any significant recall period effect on PF8c responses. Therefore, we recommend the use of the PROMIS physical function standard, with no specified recall time period.

The Development of iManage-PC, an Online Symptom Monitoring and Self-management Tool for Men With Clinically Localized Prostate Cancer.

BACKGROUND: Prostate cancer (PC) often impacts 4 major aspects of health-related quality of life (HRQL): urinary, sexual, and bowel dysfunction, and anxiety. Online tools may be helpful in supporting the development of self-management skills that can improve HRQL. OBJECTIVE: The aim of this study was to develop and pilot-test an online symptom monitoring and self-management program, iManage-PC. METHODS: A literature search, input from experts, and feedback from patients were used to develop iManage-PC. A 4-week, single-arm pilot study was conducted with 96 men with prostate cancer. We evaluated system usability, acceptance, and satisfaction and examined preliminary effects on patient-reported outcomes. RESULTS: Rates of retention (94.8%) and adherence to symptom monitoring (95.0%-97.0%) were high. Most participants rated the tool as satisfactory and acceptable (81.2%-94.3%). Related-samples Wilcoxon signed rank tests revealed that participants reported increased self-efficacy related to their ability to manage their adverse effects (T = 1772.0, P < .001, r = 0.39), physical discomfort (T = 1259.0, P < .001, r = 0.40), and stress and worry (T = 1108.5, P = .001, r = 0.34). Global mental and physical health also improved (T = 1322.0, P = .032, r = 0.23, and T = 1409.0, P = .001, r = 0.35, respectively). CONCLUSIONS: Future research with such tools should examine the potential role of cut-score-derived management interventions to improve engagement, symptom management self-efficacy, and HRQL. IMPLICATIONS FOR PRACTICE: Our findings are consistent with a growing body of literature that supports the feasibility and acceptability of remotely delivered interventions.

Can the Knee Outcome and Osteoarthritis Score (KOOS) Function Subscale Be Linked to the PROMIS Physical Function to Crosswalk Equivalent Scores?

BACKGROUND: An increased focus on patient-reported outcome measures (PROMs) has led to a proliferation of these measures in orthopaedic surgery. Mandating a single PROM in clinical and research orthopaedics is not feasible given the breadth of data already collected with older measures and the emergence of psychometrically superior measures. Creating crosswalk tables for scores between measures allows providers to maintain control of measure choice. Furthermore, crosswalk tables permit providers to compare scores collected with older outcome measures with newly collected ones. Given the widespread use of the newer Patient-reported Outcome Measure Information System Physical Function (PROMIS PF) and the established Knee Outcome and Osteoarthritis Score (KOOS), it would be clinically useful to link these two measures. QUESTION/PURPOSE: Can the KOOS Function in Activities of Daily Living (ADL) subscale be robustly linked to the PROMIS PF to create a crosswalk table of equivalent scores that accurately reflects a patient's reported physical function level on both scales? METHODS: We sought to establish a common standardized metric for collected responses to the PROMIS PF and the KOOS ADL to develop equations for converting a PROMIS PF score to a score for the KOOS-ADL subscale and vice versa. To do this, we performed a retrospective, observational study at two academic medical centers and two community hospitals in an urban and suburban healthcare system. Patients 18 years and older who underwent TKA were identified. Between January 2017 and July 2020, we treated 8165 patients with a TKA, 93% of whom had a diagnosis of primary osteoarthritis. Of those, we considered patients who had completed a full KOOS and PROMIS PF 10a on the same date as potentially eligible. Twenty-one percent (1708 of 8165) of patients were excluded because no PROMs were collected at any point, and another 67% (5454 of 8165) were excluded because they completed only one of the required PROMs, leaving 12% (1003 of 8165) for analysis here. PROMs were collected each time they visited the health system before and after their TKAs. Physical function was measured by the PROMIS PF version 1.0 SF 10a and KOOS ADL scale. Analyses to accurately create a crosswalk of equivalent scores between the measures were performed using the equipercentile linking method with both unsmoothed and log linear smoothed score distributions. RESULTS: Crosswalks were created, and adequate validation results supported their validity; we also created tables to allow clinicians and clinician scientists to convert individual patients' scores easily. The mean difference between the observed PROMIS PF scores and the scores converted by the crosswalk from the KOOS-ADL scores was -0.08 ± 4.82. A sensitivity analysis was conducted, confirming the effectiveness of these crosswalks to link the scores of two measures from patients both before and after surgery. CONCLUSION: The PROMIS PF 10a can be robustly linked to the KOOS ADL measure. The developed crosswalk table can be used to convert PROMIS PF scores from KOOS ADL and vice versa. CLINICAL RELEVANCE: The creation of a crosswalk table between the KOOS Function in ADL subscale and PROMIS PF allows clinicians and researchers to easily convert scores between the measures, thus permitting greater choice in PROM selection while preserving comparability between patient cohorts and PROM data collected from older outcome measures. Creating a crosswalk, or concordance table, between the two scales will facilitate this comparison, especially when pooling data for meta-analyses.

Establishing a common metric for patient-reported outcomes in cancer patients: linking patient reported outcomes measurement information system (PROMIS), numerical rating scale, and patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE).

BACKGROUND: Researchers and clinicians studying symptoms experienced by people with cancer must choose from various scales. It would be useful to know how the scores on one measure translate to another. METHODS: Using item response theory (IRT) with the single-group design, in which the same sample answers all measures, we produced crosswalk tables linking five 0-10 numeric rating scale (NRS) and 15 items from Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE, scored on a 1-5 scale) to the T-Score metric of six different scales from the NIH Patient reported Outcomes Measurement Information System (PROMIS®). The constructs, for which we conducted linking, include emotional distress-anxiety, emotional distress-depression, fatigue, sleep disturbance, pain intensity, and pain interference. We tested the IRT linking assumption of construct similarity between measures by comparing item content and testing unidimensionality of item sets comprising each construct. We also investigated the correlation of the measures to be linked and, by inspecting standardized mean differences, whether the linkage is invariant across age and gender subgroups. For measures that satisfied the assumptions, we conducted linking. RESULTS: In general, an NRS score of 0 corresponded to about 38.2 on the PROMIS T-Score scale (mean = 50; SD = 10); whereas an NRS score of 10 corresponded to a PROMIS T-Score of approximately 72.7. Similarly, the lowest/best score of 1 on PRO-CTCAE corresponded to 39.8 on T-score scale and the highest/worst score of 5 corresponded to 72.0. CONCLUSION: We produced robust linking between single item symptom measures and PROMIS short forms.

Assessing meaning & purpose in life: development and validation of an item bank and short forms for the NIH PROMIS®.

PURPOSE: A sense of meaning and purpose is important for people living with acute and chronic illness. It can buffer the effects of stress and facilitate adaptive coping. As part of the Patient-Reported Outcomes Measurement Information System (PROMIS), we developed and validated an item response theory (IRT)-based measure of meaning and purpose in life. METHODS: Informed by a literature review and patient and content-expert input, we wrote 52 items to assess meaning and purpose and administered them to a general population sample (n = 1000) along with the Meaning in Life Questionnaire-Presence of Meaning Subscale (MLQ-Presence) and the Life Engagement Test (LET). We split the sample in half for exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). IRT analyses included assessments of differential item functioning (DIF). RESULTS: Participants had a mean age of 47.8 years and 50.3% were male. EFA revealed one dominant factor and CFA yielded a good fitting model for a 37-item bank (CFI = 0.962, TLI = 0.960, RMSEA = 0.085). All items were free of sex, age, education, and race DIF. Internal consistency reliability estimates ranged from α = 0.90 (4-item short form) to α = 0.98 (37-item bank). The 8-item Meaning and Purpose short form was correlated with the MLQ-Presence (r = 0.89), the LET (r = 0.79), and the full PROMIS Meaning and Purpose item bank (r = 0.98). CONCLUSIONS: The PROMIS Meaning and Purpose measures demonstrated sufficient unidimensionality and displayed good internal consistency, model fit, and convergent validity. Further psychometric testing of the PROMIS Meaning and Purpose item bank and short forms in people with chronic diseases will help evaluate the generalizability of this new tool.

Calibration and initial validation of a general self-efficacy item bank and short form for the NIH PROMIS®.

AIMS: General self-efficacy is associated with adaptive coping and positive health outcomes. The Patient-Reported Outcomes Measurement Information System (PROMIS®) has developed self-efficacy item banks for managing chronic conditions, but lacks a general self-efficacy measure. We sought to refine and validate an item-response theory (IRT)-based measure of general self-efficacy for PROMIS®. METHODS: Ten items were modified from the NIH Toolbox® Self-Efficacy Item Bank by creating "confidence" response options, and administered to a general population sample (n = 1000) with the Toolbox® Self-Efficacy Item Bank, Life Orientation Test-Revised (LOT-R), and Generalized Expectancy for Success Scale (GESS). We split the sample in half for exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). IRT analyses included evaluation of differential item functioning (DIF). RESULTS: Participants had a mean age of 47.8 years and 50.3% were male. EFA showed all items loaded onto one dominant factor and CFA yielded a good fitting model for a general self-efficacy bank with confidence response options (CFI = 0.987, TLI = 0.984, RMSEA = 0.090). Items showed no evidence of DIF by gender, age, education, or race. Internal consistency reliability was α = .94 and .88 for a new 10-item general self-efficacy bank and 4-item short form, respectively. The new bank was correlated with the LOT-R (r = .58), the GESS (r = .55), and the Toolbox® Self-Efficacy Item Bank (r = .87). CONCLUSIONS: The PROMIS® General Self-Efficacy measure demonstrated sufficient unidimensionality and displayed good internal consistency reliability, model fit, and convergent validity. Further psychometric testing of the PROMIS® General Self-Efficacy Item Bank and Short Form can evaluate its utility in people with chronic health conditions.

Establishing a common metric for self-reported anxiety in patients with prostate cancer: Linking the Memorial Anxiety Scale for Prostate Cancer with PROMIS Anxiety.

BACKGROUND: Anxiety is a common patient concern and clinical endpoint in prostate cancer outcomes research. It is measured using different self-report instruments that are not directly comparable, thereby making clinical trials, clinical performance measurement, and comparative effectiveness research challenging when anxiety is the outcome of interest. The objective of the current study was to enable a common reporting metric of anxiety so that scores on commonly used anxiety measures could be converted into Patient-Reported Outcomes Measurement Information System (PROMIS) scores for ease of application, interpretation, and comparability. METHODS: Using an internet health panel, a total of 806 men with clinically localized prostate cancer completed items from the National Institutes of Health PROMIS Anxiety Short Form (version 7a) and the 18-item Memorial Anxiety Scale for Prostate Cancer (MAX-PC). A common metric was created using analyses based on item response theory, producing score crosswalk tables. The linking relationships were evaluated by resampling small subsets and estimating confidence intervals for the differences between the observed and linked PROMIS scores. RESULTS: Results of factor analysis and item response theory model fit supported the hypothesis that both scales measure essentially the same concept. Therefore, crosswalk tables appear to be justified and increasingly robust with increasing sample sizes. CONCLUSIONS: MAX-PC Anxiety results can be expressed on the PROMIS Anxiety metric for the purposes of clinical performance measurement, clinical trial outcomes, comparative effectiveness research, and other efforts to compare anxiety results across studies that use any one of these measures.

Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

BACKGROUND: Measuring patient-reported outcomes (PROs) is becoming an integral component of quality improvement initiatives, clinical care, and research studies in cancer, including comparative effectiveness research. However, the number of PROs limits comparability across studies. Herein, the authors attempted to link the Functional Assessment of Cancer Therapy-General Physical Well-Being (FACT-G PWB) subscale with the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) calibrated item bank. The also sought to augment a subset of the conceptually most similar FACT-G PWB items with PROMIS PF items to improve the linking. METHODS: Baseline data from 5506 participants in the Measuring Your Health (MY-Health) study were used to identify the optimal items for linking FACT-G PWB with PROMIS PF. A mixed methods approach identified the optimal items for creating the 5-item FACT/PROMIS-PF5 scale. Both the linked and augmented relationships were cross-validated using the follow-up MY-Health data. RESULTS: A 5-item FACT-G PWB item subset was found to be optimal for linking with PROMIS PF. In addition, a 2-item subset, including only items that were conceptually very similar to the PROMIS item bank content, were augmented with 3 PROMIS PF items. This new FACT/PROMIS-PF5 provided superior score recovery. CONCLUSIONS: The PROMIS PF metric allows for the evaluation of the extent to which similar questionnaires can be linked and therefore expressed on the same metric. These results allow for the aggregation of existing data and provide an optimal measure for future studies wishing to use the FACT yet also report on the PROMIS PF metric. Cancer 2018;124:153-60. © 2017 American Cancer Society.

Factors Affecting Quality of Life at Different Intervals After Treatment of Localized Prostate Cancer: Unique Influence of Treatment Decision Making Satisfaction, Personality and Sexual Functioning.

PURPOSE: Using patient reported outcomes measures we identified the most informative set of factors associated with quality of life in a large sample of men treated for localized prostate cancer. MATERIALS AND METHODS: We examined relationships with quality of life using FACIT (Functional Assessment of Chronic Illness Therapy). We also hypothesized variables in a sample of men diagnosed with localized prostate cancer who represented different time points since treatment, including less than 12 months in 70, 1 to 3 years in 344, greater than 3 to 5 years in 291 and greater than 5 years in 97. Correlative measures included subscales of MAX-PC (Memorial Anxiety Scale for Prostate Cancer), short forms of PROMIS® and SOMS (Surgical Outcomes Measurement System), TDM-SATS (Treatment Decision-Making Satisfaction Scale) and subscales of the BFI (Big Five Inventory) of personality. RESULTS: Quality of life was significantly associated with hypothesized variables across different time cohorts. In regression models several factors accounted for most of the variability in quality of life scores depending on time since treatment, including 47%, 22%, 29% and 27% at less than 12 months, 1 to 3 years, greater than 3 to 5 years and greater than 5 years, respectively. Upon examining the unique contribution of these variables, treatment decision making satisfaction was the only variable to have a significant and unique contribution to quality of life across all 4 time cohorts (standardized coefficients 0.33, 0.27, 0.31 and 0.49, respectively, p <0.01). In the cohort with 1 to 3 years since treatment erectile function and neurotic personality style also had unique associations with quality of life (standardized coefficients 0.25 and -0.20, respectively). CONCLUSIONS: When considering the short-term and the longer term quality of life of a man after treatment for localized prostate cancer, our findings highlight the importance of treatment decision making satisfaction, erectile function and personality.

Clinical validity of PROMIS Depression, Anxiety, and Anger across diverse clinical samples.

OBJECTIVES: The purpose of this study was to evaluate the responsiveness to change of the PROMIS negative affect measures (depression, anxiety, and anger) using longitudinal data collected in six chronic health conditions. STUDY DESIGN AND SETTING: Individuals with major depressive disorder (MDD), back pain, chronic obstructive pulmonary disease (COPD), chronic heart failure (CHF), and cancer completed PROMIS negative affect instruments as computerized adaptive test or as fixed-length short form at baseline and a clinically relevant follow-up interval. Participants also completed global ratings of health. Linear mixed effects models and standardized response means (SRM) were estimated at baseline and follow-up. RESULTS: A total of 903 individuals participated (back pain, n = 218; cancer, n = 304; CHF, n = 60; COPD, n = 125; MDD, n = 196). All three negative affect instruments improved significantly for treatments of depression and pain. Depression improved for CHF patients (anxiety and anger not administered), whereas anxiety improved significantly in COPD groups (stable and exacerbation). Response to treatment was not assessed in cancer. Subgroups of patients reporting better or worse health showed a corresponding positive or negative average SRM for negative affect across samples. CONCLUSION: This study provides evidence that the PROMIS negative affect scores are sensitive to change in intervention studies in which negative affect is expected to change. These results inform the estimation of meaningful change and enable comparative effectiveness research.

Validity of PROMIS physical function measured in diverse clinical samples.

OBJECTIVES: To evaluate the validity of the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function measures using longitudinal data collected in six chronic health conditions. STUDY DESIGN AND SETTING: Individuals with rheumatoid arthritis (RA), major depressive disorder (MDD), back pain, chronic obstructive pulmonary disease (COPD), chronic heart failure (CHF), and cancer completed the PROMIS Physical Function computerized adaptive test or fixed-length short form at baseline and at the end of clinically relevant follow-up intervals. Anchor items were also administered to assess change in physical function and general health. Linear mixed-effects models and standardized response means were estimated at baseline and follow-up. RESULTS: A total of 1,415 individuals participated (COPD n = 121; CHF n = 57; back pain n = 218; MDD n = 196; RA n = 521; cancer n = 302). The PROMIS Physical Function scores improved significantly for treatment of CHF and back pain patients but not for patients with MDD or COPD. Most of the patient subsamples that reported improvement or worsening on the anchors showed a corresponding positive or negative change in PROMIS Physical Function. CONCLUSION: This study provides evidence that the PROMIS Physical Function measures are sensitive to change in intervention studies where physical function is expected to change and able to distinguish among different clinical samples. The results inform the estimation of meaningful change, enabling comparative effectiveness research.

The impact of events scale: a comparison of frequency versus severity approaches to measuring cancer-specific distress.

OBJECTIVE: The Impact of Events Scale (IES) is one of the most widely used measures of event-specific distress. The IES assesses the frequency with which respondents experience intrusive thoughts and avoidant behaviors over the past week. Our aim is to demonstrate the benefit of a severity-based measurement approach of the IES compared with a frequency-based measurement approach. METHODS: A mixed group of post-treatment cancer survivors (N = 325; M = 31.8 years old) completed measures assessing quality of life (Functional Assessment of Cancer Therapy-General), psychological adjustment (Mental Health Inventory), and cancer-related distress (IES). The IES was keyed to the cancer experience and administered with standard (frequency) and modified (severity) response options. RESULTS: Classical reliability analyses and bifactor modeling were conducted on both versions of the IES. Reliability estimates suggest that the IES severity items were more highly intercorrelated than the IES frequency items. Both versions of the IES were highly correlated (r = 0.82), showing the presence of a dominant general factor. Bifactor modeling suggested that the severity items generally provided higher levels of discrimination than the frequency items. Validity correlations with the Functional Assessment of Cancer Therapy-General and Mental Health Inventory demonstrated that the IES severity performed as good as or better than the IES frequency. CONCLUSIONS: Given the high correlations and similarity in content, the IES severity items largely assess the same construct as the IES frequency items. However, IES severity items generally showed improved psychometric properties and similar or higher correlations with quality of life and psychological adjustment. The IES severity approach appears to be a more informative method for assessing cancer-specific distress.

Psychometric and genetic architecture of substance use disorder and behavioral disinhibition measures for gene association studies.

Using large twin, family, and adoption studies conducted at the Minnesota Center for Twin and Family Research, we describe our efforts to develop measures of substance use disorder (SUD) related phenotypes for targets in genome wide association analyses. Beginning with a diverse set of relatively narrow facet-level measures, we identified 5 constructs of intermediate complexity: nicotine, alcohol consumption, alcohol dependence, illicit drug, and behavioral disinhibition. The 5 constructs were moderately correlated (mean r = .57) reflecting a general externalizing liability to substance abuse and antisocial behavior. Analyses of the twin and adoption data revealed that this general externalizing liability accounted for much of the genetic risk in each of the intermediate-level constructs, though each also exhibited significant unique genetic and environmental risk. Additional analyses revealed substantial effects for age and sex, significant shared environmental effects, and that the mechanism of these shared environmental effects operates via siblings rather than parents. Our results provide a foundation for genome wide association analyses to detect risk alleles for SUDs as well as novel insights into genetic and environmental risk for SUDs.