Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Juckett, David A.; Davis, Fred; Gostine, Mark; Reed, Philip L.; Risko, Rebecca

doi:10.1186/s12911-015-0164-4

Cited by 5 publications

(4 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, in terms of particular relevance, it has been argued that the documentation of clinical PROs - for example, as part of the phenotype “pain” - offers the chance to better align treatment options and outcomes [34].…”

Section: Discussionmentioning

confidence: 99%

Patient-reported data informing early benefit assessment of rare diseases in Germany: A systematic review

2019

View full text Add to dashboard Cite

BackgroundSince the implementation of the Regulation on Patient Integration (2003), the Act on the Reorganization of the Pharmaceutical Market (2011), and the Patient Rights Law (2013), the inclusion of patient perspectives has been further anchored in the German early benefit assessment process. During the assessment of rare disease interventions, patient perspectives are particularly important, as clinical studies are often designed acknowledging small samples and patients suffering from severe symptoms and the chronic course of the disease. Therefore, our research question is whether patient perspectives are considered as part of early benefit assessments for rare diseases. We also strive to examine how patient perspectives are methodologically elicited and presented.MethodsOur empirical evidence comes from a systematic review of orphan drug value dossiers submitted to the German Federal Joint Committee as well as the corresponding evaluations conducted between January 1, 2011 and March 1, 2019 (n = 81). Data on patient perspective integration were extracted using the following patient-reported outcome subcategories: clinical patient-reported outcomes, health-related quality of life, patient preferences, and patient satisfaction.ResultsThe analysis demonstrates the specific relevance of patient-reported outcomes raised as part of the medical data set and presented during the early benefit assessment process. They are predominantly presented in the form of health-related quality of life data (n = 75%) and clinical outcomes (n = 49%). Preferences (n = 2%) and satisfaction (n = 1%) are still rarely presented, although the heated methodological discussion in Germany would suggest otherwise. While various methodologies for the integration of clinical outcomes and quality of life data were found, presenting data on satisfaction and preferences still lacks methodological rigor. The German Federal Joint Committee has not yet integrated these data in their decision text. Clinical outcomes and quality of life have been included in 46% and 73% of the cases, respectively.ConclusionsThe underlying analysis demonstrates that there is still a relative high potential for the regular and systematic inclusion of patient perspectives within the early benefit assessment process for rare diseases. In particular, patient preferences and patient satisfaction are still rarely included suggesting the need for a clear-cut methodological foundation and incentives.

show abstract

Section: Discussionmentioning

confidence: 99%

Patient-reported data informing early benefit assessment of rare diseases in Germany: A systematic review

2019

View full text Add to dashboard Cite

show abstract

“…Therefore, patients with FM in the ProCare Systems’ network of clinics from January 1999 to February 17, 2015 were identified as previously described: either 1 year of physician-assigned ICD-9 code 729.1 (“myositis and myalgia, unspecified”) with two codes separated at least 1 year apart and a length of treatment ≥365 days, or using a predictive model. 9 , 19 Patients were also required to have a combination of more than two office visits, Pain Health Assessments (PHA; ProCare Systems, Inc.; a patient self-assessment instrument) or prescription medications used to treat FM.…”

Section: Methodsmentioning

confidence: 99%

Characterizing classes of fibromyalgia within the continuum of central sensitization syndrome

Davis¹,

Gostine²,

Roberts³

et al. 2018

JPR

Self Cite

View full text Add to dashboard Cite

BackgroundWhile fibromyalgia (FM) is characterized by chronic widespread pain and tenderness, its presentation among patients as a continuum of diseases rather than a single disease contributes to the challenges of diagnosis and treatment. The purpose of this analysis was to distinguish and characterize classes of FM within the continuum using data from chronic pain patients.MethodsFM patients were identified from administrative claims data from the ProCare Systems’ network of Michigan pain clinics between January 1999 and February 2015. Identification was based on either use of traditional criteria (ie, ICD-9 codes) or a predictive model indicative of patients having FM. Patients were classified based on similarity of comorbidities (symptom severity), region of pain (widespread pain), and type and number of procedures (treatment intensity) using unsupervised learning. Text mining and a review of physician notes were conducted to assist in understanding the FM continuum.ResultsA total of 2,529 FM patients with 79,570 observations or clinical visits were evaluated. Four main classes of FM patients were identified: Class 1) regional FM with classic symptoms; Class 2) generalized FM with increasing widespread pain and some additional symptoms; Class 3) FM with advanced and associated conditions, increasing widespread pain, increased sleep disturbance, and chemical sensitivity; and Class 4) FM secondary to other conditions.ConclusionFM is a disease continuum characterized by progressive and identifiable classifications. Four classes of FM can be differentiated by pain and symptom severity, specific comorbidities, and use of clinical procedures.

show abstract

“…Outcomes evaluated included comorbidities, musculoskeletal procedures, and body regions of pain associated with FM. Additionally, items from the PRISM™ PHA (ProCare Systems Inc.) were also used to investigate measures such as functional and psychosocial impairment, pain, fatigue, and quality of sleep. PRISM™ is a patient self‐assessment instrument that captures demographic information, and medical and social history.…”

Section: Methodsmentioning

confidence: 99%

Clinical Characteristics of Fibromyalgia in a Chronic Pain Population

Gostine

Davis²,

Roberts³

et al. 2017

Pain Practice

Self Cite

View full text Add to dashboard Cite

Objective: To compare fibromyalgia (FM) characteristics among patients identified in a community-based chronic pain cohort based on traditional International Classification of Diagnoses 9th revision (ICD-9) diagnostic coding, with that of patients identified using a novel predictive model. Methods: This retrospective study used data collected from July 1999 to February 17, 2015, in multiple chronic pain clinics in the United States. Patients were assigned to the FM case group based on specific inclusion criteria using ICD-9 codes or, separately, from results of a novel FM predictive model that was developed using random forest and logistic regression techniques. Propensity scoring (1:1) matched FM patients (cases) to nonmalignant chronic pain patients without FM (controls). Patient-reported measures (eg, pain, fatigue, quality of sleep) and clinical characteristics (ie, comorbidities, procedures, and regions of pain) were outcomes for analysis.Results: Nine ICD-9 clinical modification diagnoses had odds ratios with large effect sizes (Cohen's d > 0.8), demonstrating the magnitude of the difference between the FM and matched non-FM cohorts: chronic pain syndrome, latex allergy, muscle spasm, fasciitis, cervicalgia, thoracic pain, shoulder pain, arthritis, and cervical disorders (all P < 0.0001). Six diagnoses were found to have a moderate effect size (Cohen's 0.5 < d > 0.8): cystitis, cervical degeneration, anxiety, joint pain, lumbago, and cervical radiculitis. Conclusions: The identification of multiple comorbidities, diagnoses, and musculoskeletal procedures that were significantly associated with FM may facilitate differentiation of FM patients from other conditions characterized by chronic widespread pain. Predictive modeling may enhance identification of FM patients who may otherwise go undiagnosed. &

show abstract

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Cited by 5 publications

References 34 publications

Patient-reported data informing early benefit assessment of rare diseases in Germany: A systematic review

Patient-reported data informing early benefit assessment of rare diseases in Germany: A systematic review

Characterizing classes of fibromyalgia within the continuum of central sensitization syndrome

Clinical Characteristics of Fibromyalgia in a Chronic Pain Population

Contact Info

Product

Resources

About