Correlation between pain response and improvements in patient-reported outcomes and health-related quality of life in duloxetine-treated patients with diabetic peripheral neuropathic pain

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

BACKGROUND

Rapid digitalization in health care has led to the adoption of digital technologies; however, limited trust in internet-based health decisions and the need for technical personnel hinder the use of smartphones and machine learning applications. To address this, automated machine learning (AutoML) is a promising tool that can empower health care professionals to enhance the effectiveness of mobile health apps.

OBJECTIVE

We used AutoML to analyze data from clinical studies involving patients with chronic hand and/or foot eczema or psoriasis vulgaris who used a smartphone monitoring app. The analysis focused on itching, pain, Dermatology Life Quality Index (DLQI) development, and app use.

METHODS

After extensive data set preparation, which consisted of combining 3 primary data sets by extracting common features and by computing new features, a new pseudonymized secondary data set with a total of 368 patients was created. Next, multiple machine learning classification models were built during AutoML processing, with the most accurate models ultimately selected for further data set analysis.

RESULTS

Itching development for 6 months was accurately modeled using the light gradient boosted trees classifier model (log loss: 0.9302 for validation, 1.0193 for cross-validation, and 0.9167 for holdout). Pain development for 6 months was assessed using the random forest classifier model (log loss: 1.1799 for validation, 1.1561 for cross-validation, and 1.0976 for holdout). Then, the random forest classifier model (log loss: 1.3670 for validation, 1.4354 for cross-validation, and 1.3974 for holdout) was used again to estimate the DLQI development for 6 months. Finally, app use was analyzed using an elastic net blender model (area under the curve: 0.6567 for validation, 0.6207 for cross-validation, and 0.7232 for holdout). Influential feature correlations were identified, including BMI, age, disease activity, DLQI, and Hospital Anxiety and Depression Scale-Anxiety scores at follow-up. App use increased with BMI >35, was less common in patients aged >47 years and those aged 23 to 31 years, and was more common in those with higher disease activity. A Hospital Anxiety and Depression Scale-Anxiety score >8 had a slightly positive effect on app use.

CONCLUSIONS

This study provides valuable insights into the relationship between data characteristics and targeted outcomes in patients with chronic eczema or psoriasis, highlighting the potential of smartphone and AutoML techniques in improving chronic disease management and patient care.

Relationship Between Pain Alleviation and Disease-specific Health-related Quality of Life Measures in Patients With Chronic Low Back Pain Receiving Duloxetine: Exploratory Post Hoc Analysis of a Japanese Phase 3 Randomized Study

This post hoc analysis of a Japanese phase 3 randomized study (ClinicalTrials.gov identifier: NCT01855919) investigated relationships between pain severity (assessed by the Brief Pain Inventory [BPI]) and disease-specific health-related quality of life (assessed by the 24-item Roland-Morris Disability Questionnaire [RDQ-24]) in duloxetine-treated patients with chronic low back pain (CLBP).

The Clinical Relevance of Pain Severity Changes: Is There Any Difference Between Asian and Caucasian Patients With Osteoarthritis Pain?

The objective of the present analysis was to determine whether changes in Brief Pain Inventory (BPI) average pain scores by patient global impression of improvement (PGI‐I) category and the cut‐off for clinically important difference (CID) were different between Asian and Caucasian patients with chronic pain due to osteoarthritis. This analysis used data from 3 (Caucasian) and 2 (Asian) randomized, placebo‐controlled, 10‐ to 14‐week duloxetine studies for the treatment of patients ≥40 years of age with osteoarthritis pain. The receiver operating characteristic (ROC) analysis was used to characterize the association between changes in BPI average pain scores and PGI‐I levels at study endpoint. The CID was characterized by PGI‐I, and the cut‐off point for CID in BPI average pain scores was determined by the intersection of a 45‐degree tangent line with each ROC curve. Data from 668 Asian and 868 Caucasian patients were available for analysis. Baseline BPI average pain ratings including worst and least pain were comparable between Asians and Caucasians. Ratings for percentage change from baseline to endpoint for BPI average pain scores in Asian patients and Caucasian patients were similar across the 7 PGI‐I categories, regardless of age, gender, study, and treatment. The ROC analysis results of cut‐off points in BPI average pain scores demonstrated the raw change cut‐off was −3.0, and percentage change cut‐off was −40% for both Asian and Caucasian patients. Overall, the present analysis concludes changes in BPI average pain scores by PGI‐I category and the cut‐off for CID were similar for Asian and Caucasian patients with chronic pain due to osteoarthritis.

Health-related quality of life in people with type 2 diabetes participating in the LEADER trial

AIMS

To assess health-related quality of life (HRQoL) in people with type 2 diabetes (T2D) participating in the LEADER cardiovascular outcomes trial using the five-dimension European Quality of Life questionnaire (EQ-5D).

MATERIALS AND METHODS

The EQ-5D was administered every 12 months in a subset of patients from Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain, Sweden, the United Kingdom and the United States. We compared changes in utility index scores and visual analogue scale (VAS) scores from baseline to 36 months in participants treated with liraglutide and placebo. We also assessed which complications had the greatest impact on quality of life.

RESULTS

At 36 months, less deterioration in EQ-5D utility index score was seen in the liraglutide group (-0.058) than in the placebo group (-0.082; estimated treatment difference [ETD] 0.023, 95% confidence interval [CI] 0.004;0.043; P = 0.020). A smaller decrease in EQ-5D VAS score was also demonstrated in the liraglutide group (-3.51) vs. the placebo group (-5.45; ETD 1.94, 95% CI 0.32;3.57; P = 0.019). The benefits of liraglutide treatment compared with placebo were driven primarily by shifts in the domains of mobility and self-care. The most influential events contributing to poorer HRQoL were stroke, heart failure, malignant neoplasm and confirmed hypoglycaemia.

CONCLUSIONS

Liraglutide demonstrated a modest but significant benefit in patient-reported health status using the EQ-5D, compared with placebo. This benefit may be of clinical relevance and requires further study.

Neuropathic pain

Neuropathic pain is caused by a lesion or disease of the somatosensory system, including peripheral fibres (Aβ, Aδ and C fibres) and central neurons, and affects 7-10% of the general population. Multiple causes of neuropathic pain have been described and its incidence is likely to increase owing to the ageing global population, increased incidence of diabetes mellitus and improved survival from cancer after chemotherapy. Indeed, imbalances between excitatory and inhibitory somatosensory signalling, alterations in ion channels and variability in the way that pain messages are modulated in the central nervous system all have been implicated in neuropathic pain. The burden of chronic neuropathic pain seems to be related to the complexity of neuropathic symptoms, poor outcomes and difficult treatment decisions. Importantly, quality of life is impaired in patients with neuropathic pain owing to increased drug prescriptions and visits to health care providers, as well as the morbidity from the pain itself and the inciting disease. Despite challenges, progress in the understanding of the pathophysiology of neuropathic pain is spurring the development of new diagnostic procedures and personalized interventions, which emphasize the need for a multidisciplinary approach to the management of neuropathic pain.

Neuropathic pain

Neuropathic pain is caused by a lesion or disease of the somatosensory system, including peripheral fibres (Aβ, Aδ and C fibres) and central neurons, and affects 7-10% of the general population. Multiple causes of neuropathic pain have been described and its incidence is likely to increase owing to the ageing global population, increased incidence of diabetes mellitus and improved survival from cancer after chemotherapy. Indeed, imbalances between excitatory and inhibitory somatosensory signalling, alterations in ion channels and variability in the way that pain messages are modulated in the central nervous system all have been implicated in neuropathic pain. The burden of chronic neuropathic pain seems to be related to the complexity of neuropathic symptoms, poor outcomes and difficult treatment decisions. Importantly, quality of life is impaired in patients with neuropathic pain owing to increased drug prescriptions and visits to health care providers, as well as the morbidity from the pain itself and the inciting disease. Despite challenges, progress in the understanding of the pathophysiology of neuropathic pain is spurring the development of new diagnostic procedures and personalized interventions, which emphasize the need for a multidisciplinary approach to the management of neuropathic pain.