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Identifying optimal stratification techniques for subgrouping patients with low back pain (LBP) into treatment groups for the purpose of identifying optimal management and improving clinical outcomes is an important area for further research. Our study aimed to compare performance of the STarT Back Tool (SBT) and 3 stratification techniques involving PROMIS domain scores for use in patients presenting to a spine clinic for chronic LBP. Retrospective cohort study. Adult patients with chronic LBP seen in a spine center between November 14, 2018 and May 14, 2019 who completed patient-reported outcomes (PROs) as part of routine care, and were followed up with completed PROs 1 year later. Four stratification techniques, including SBT, and 3 PROMIS-based techniques: the NIH Task Force recommended Impact Stratification Score (ISS), symptom clusters based on latent class analysis (LCA), and SPADE symptom clusters. The 4 stratification techniques were compared according to criterion validity, construct validity, and prognostic utility. For criterion validity, overlap in characterization of mild, moderate, and severe subgroups were compared to SBT, which was considered the gold standard, using quadratic weighted kappa statistic. Construct validity compared techniques' ability to differentiate across disability groups defined by modified Oswestry LBP Disability Questionnaire (MDQ), median days in the past month unable to complete activities of daily living (ADLs), and worker's compensation using standardized mean differences (SMD). Prognostic utility was compared based on the techniques' ability to predict long-term improvement in outcomes, defined as improvement in global health and MDQ at 1-year. There were 2,246 adult patients with chronic LBP included in our study (mean age 61.0 [SD 14.0], 55.0% female, 83.4% white). All stratification techniques resulted in roughly a third of patients grouped into mild, moderate, and severe categories, with ISS and LCA demonstrating substantial agreement with SBT, while SPADE had moderate agreement. Construct validity was met for all techniques, with large effects demonstrated between mild and severe categories for differentiating MDQ, ADLs, and worker's compensation disability groups (SMD range 0.57–2.48). All stratification techniques demonstrated ability to detect improvement by 1-year, with severe groups experiencing the greatest improvement in multivariable logistic regression models. All 4 stratification techniques demonstrated validity and prognostic utility for subgrouping patients with chronic LBP based on risk of long-term disability. ISS and LCA symptom clusters may be the optimal methods given the improved feasibility of including only a few relevant PROMIS domains. Future research should investigate multidisciplinary treatment approaches to target mild, moderate, and severe patients based on these techniques. [ABSTRACT FROM AUTHOR]

Purpose: Patient-reported outcome measures (PROMs), including global health and construct-specific measures, are collected across healthcare systems. Efforts should be made to reduce data collection burden and individualize survey administration to patient needs. Our study evaluated the ability of utilizing items on a global health measure to identify patients who may require additional screening. Methods: A cross-sectional study was conducted of patients who completed PROMIS Global Health (GH) as part of routine care, as well as additional construct-specific surveys, in a large healthcare system from 1/1/2016 to 12/31/2018. Receiver operating characteristic (ROC) analysis identified optimal thresholds for PROMIS GH items identifying clinically meaningful thresholds on construct-specific PROMs: PHQ-9 score ≥10, Neuro-QoL Cognitive Function, PROMIS Physical Function, and Satisfaction with Social Roles and Activities T-score ≤40, PROMIS Anxiety, Fatigue, Sleep Disturbance, and Pain Interference T-score ≥60. Results: There were 206,685 patients who completed PROMIS GH and additional construct-specific surveys. Scores ≤3 on PROMIS GH item 10 (emotional problems) had 90.0% sensitivity (area under the curve (AUC) = 0.821) for identifying patients with moderate-severe depressive symptoms on PHQ-9. Similarly high sensitivities and AUCs were demonstrated for PROMIS GH items assessing mental and physical health, fatigue, and pain to identify poor scores on their corresponding construct-specific PROMs. Conclusions: Our study provides preliminary support for the ability of utilizing PROMIS GH items as screening tools to identify patients with poor scores on additional construct-specific PROMs. Through directing construct-specific PROMs to patients for whom they are most applicable, survey burden could be reduced for many patients, allowing a more efficient and targeted use of PROMs in healthcare decision-making. [ABSTRACT FROM AUTHOR]

Purpose: The Modified Low Back Pain Disability Questionnaire (MDQ) is a commonly used tool to assess functioning of patients with low back pain (LBP). Recently, the Patient-Reported Outcomes Measurement Information System (PROMIS) was suggested as an alternative platform to assess LBP patient-reported health. We sought to map between the MDQ and PROMIS Physical Function (PROMIS-PF) and Pain Interference (PROMIS-PI) scales using multiple methods.Methods: In a retrospective analysis of LBP patients seen at Cleveland Clinic 11/14/18-12/11/19, T-scores from each PROMIS scale were mapped to MDQ total score individually and together. MDQ item and total scores were mapped to each PROMIS scale. Linear regression as well as linear and equipercentile equating were used. Split sample internal validation using root mean squared error (RMSE), mean absolute error (MAE), and correlations were used to assess accuracy of mapping equations.Results: 13585 patients completed the three scales. In the derivation cohort, average age was 59.0 (SD = 15.8); 53.3% female and 82.9% white. Average MDQ total, PROMIS-PF, and PROMIS-PI T-scores were 40.3 (SD = 19.0), 37.2 (SD = 7.6), and 62.9 (SD = 7.2), respectively. For estimating MDQ total scores, methods that used both PROMIS-PF and PROMIS-PI had closest estimated means, lowest RMSE and MAE, and highest correlations. For estimating each of PROMIS-PF and PROMIS-PI T-scores, the best performing method was equipercentile equating using the MDQ items.Conclusions: We created and internally validated maps between MDQ and PROMIS-PF and PROMIS-PI using linear regression, linear and equipercentile equating. Our equations can be used by researchers wishing to translate scores between these scales. [ABSTRACT FROM AUTHOR]

Background Context: Improving prognostic stratification for patients with low back pain (LBP) outside of a primary care setting has been identified as an important area for further research.Purpose: Our study aimed to identify clinical symptom classes of patients presenting to a spine clinic based on 4 Patient Reported Outcome Measurement Information System (PROMIS) domains and evaluate demographic and clinical differences across classes.Study Design: An observational cross-sectional study of patients seen in spine centers at a large health system.Patient Sample: Adult patients with LBP seen in a spine center between November 14, 2018 and May 14, 2019 who completed patient-reported outcomes as part of routine care.Outcome Measures: PROMIS physical function, pain interference, satisfaction with social roles and activities, and fatigue.Methods: Latent class analysis identified symptom classes based on PROMIS domain scores ≥1 standard deviation worse (meaningfully worse) than the general population. A multivariable multinomial logistic regression model was constructed to evaluate differences in symptom classes based on demographics and socioeconomic characteristics. Lastly, the ability of the profiles to discriminate across levels of disability, based on the modified Oswestry Disability Questionnaire (ODI), was evaluated.Results: There were 7,144 adult patients included in the study who visited spine clinics for a primary complaint of LBP and completed all 4 PROMIS domains (age 58.7±15.9, 54% female). Three distinct classes were identified. Class 1 ("Significant Symptoms," n=3238) had PROMIS scores that were meaningfully worse than the population average for all domains. Class 2 ("Mixed Symptoms," n=1366) had meaningfully worse scores on physical function and pain interference but average scores on other domains. Class 3 ("Mild Symptoms," n=2540) had average scores across all domains. Compared to patients in Class 3, those in Class 2 were more likely older, and those in Classes 1 and 2 were more likely to be divorced, have lower household income, and no employment. Level of disability was significantly different across each class (average (SD) ODI for Classes 1-3: 53.4 (14.3), 39.9 (12.5), 22.9 (12.1), p<.01).Conclusions: Patients presenting to specialty clinics for LBP demonstrate distinct clinical symptom classes which could be utilized to inform specific symptom-based treatment. Future research should evaluate the ability of these classes to predict long-term disability. [ABSTRACT FROM AUTHOR]

Importance: Long-term health effects have been indicated following COVID-19; however, the impact of COVID-19 on health-related quality of life (HRQOL), including who may experience ongoing symptoms, is unknown. Objective: To identify change in HRQOL following COVID-19 compared to pre-infection HRQOL and a matched control group, and identify predictors of patients who worsen. Design: Retrospective pre-post cohort study with a matched control group. Setting: Large healthcare system in northeast Ohio. Participants: A total of 3,690 adult patients diagnosed with COVID-19 who completed HRQOL surveys during routine care for ambulatory visits before and after infection. Propensity-score 1:1 match was utilized to identify controls without COVID who completed HRQOL at two time points. Main Outcomes: HRQOL was assessed with PROMIS Global Health: global mental and physical health summary scores. Pre- and post-COVID PROMIS Global Health was completed as part of routine care from 1/1/2019 to 2/29/2020 and 4/4/2020 to 11/1/2021, respectively, and extracted from the electronic health record. Results: COVID-19 patients (mean age 53±15; 66% female) completed PROMIS Global Health in the year prior (median 11.1 months) and after diagnosis (median 7.8 months). Compared to before infection, COVID-19 patients had a significant reduction in global mental health and stable global physical health (−0.85 and 0.05 T-score points, respectively) with clinically meaningful reduction (≥5 T-score points) experienced by 27% and 23% of patients, respectively. Predictors of worsening global health included being female, having depression, being hospitalized for COVID-19, and better pre-COVID global health. Compared to the control group, there was significantly worse global mental and physical health decline following COVID-19 (−0.53 and −0.37 T-score points, respectively). Conclusions and Relevance: A quarter of patients with COVID-19 experienced meaningful reductions in HRQOL. Reductions in global mental and physical health were modest, although significantly worse than a control group. Additionally, identified predictors of patients who worsen may assist clinicians when counseling patients of their risk of worse HRQOL following COVID-19. [ABSTRACT FROM AUTHOR]

Purpose: Caregivers, or proxies, often complete patient-reported outcome measures (PROMs) on behalf of patients with stroke. The objective of our study was to assess the validity and responsiveness of proxy-responses compared to patient-responses across multiple domains of health. Methods: Stroke patients and their proxies were recruited to complete PROMs between 7/2018–11/2019. PROMs included Neuro-QoL cognitive function, PROMIS physical function, satisfaction with social roles, anxiety, fatigue, pain interference, sleep disturbance, Global Health, and PHQ-9. Internal consistency and convergent validity were compared between patient- and proxy-reported measures. Known-groups validity was assessed across levels of stroke disability. Internal responsiveness was evaluated using paired t-tests for a subset of patients who attended rehabilitation following stroke. Analyses were stratified by patients ≤ 3 vs > 3 months from stroke. Results: This cross-sectional study included 200 stroke patients (age 62.2 ± 13.3, 41.5% female) and their proxies (age 56.5 ± 13.9, 70% female, 72% spouses). PROMs had high internal consistency and were significantly correlated for patients and proxies. Patient- and proxy-reported measures worsened with increasing stroke disability. For 34 (17%) patients who attended rehabilitation, patients self-reported improvement on 5 domains whereas proxies reported no improvement. Compared to patient self-reports, validity was worse for proxy-reports on patients ≤ 3 months but better > 3 months from stroke. Conclusions: Both patient- and proxy-reported PROMs demonstrated strong validity. Only patient-reported PROMs were responsive to change, and proxies had worse validity for patients ≤ 3 months from stroke but better validity for patients > 3 months from stroke. These findings justify the utilization of proxy responses in stroke patients > 3 months from stroke. [ABSTRACT FROM AUTHOR]

As the implementation of Patient-Reported Outcomes Measurement Information System (PROMIS) scales has increased, so has the number of studies linking legacy scale scores to PROMIS scale scores. Variability in linked scores for a given PROMIS score can be considerable, leading to potential bias. An alternative method is imputation using a bridge study. We sought to compare linking to this alternative novel method in group-level analyses using linked legacy scores. Adult patients who completed PROMIS Depression and Patient Health Questionnaire (PHQ-9) were included. We randomly allocated data samples to be missing either PROMIS Depression or PHQ-9. We estimated PROMIS T scores using six methods: Linking methods by Choi et al. (2014), linking in our internal data, imputation using bridge study data from external data and from our internal data, each with and without patient demographics. Estimated mean PROMIS T scores using the linking and imputation methods were compared to actual PROMIS T scores across varying proportions of missingness and sample size. We also compared regression coefficients for the six estimation methods to a model using actual PROMIS T scores. Mean estimated versus actual PROMIS T scores varied between 1 and 4 points for the linking methods and within 0.4 points for the imputation method using internal data with patient demographics. The imputation methods had estimated regression coefficients closer to that of the model using actual scores as compared to the linking methods. For group-level analyses, imputation using a bridge study may be a feasible alternative to using linked scores or can be used as a sensitivity analysis. Public Significance Statement: Many legacy scales have been linked to associated PROMIS scales using item response theory and other linking strategies. Group-level analyses involving such linked scores sometimes result in biased parameter estimates. We propose an alternative analysis approach: Imputation using a bridge study. The study findings indicate that imputation using a bridge study may be a feasible alternative to analyzing legacy scale data scored on a PROMIS metric. [ABSTRACT FROM AUTHOR]