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Fulltext Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches

Teoh YX, Lai KW, Usman J, Goh SL, Mohafez H, Hasikin K, et al.

J Healthc Eng, 2022;2022:4138666.
PMID: 35222885 DOI: 10.1155/2022/4138666

Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.
Fulltext Identifying placebo responders and predictors of response in osteoarthritis: a protocol for individual patient data meta-analysis

Fu Y, Persson MS, Bhattacharya A, Goh SL, Stocks J, van Middelkoop M, et al.

Syst Rev, 2016 10 28;5(1):183.
PMID: 27793184

BACKGROUND: The management of osteoarthritis (OA) is unsatisfactory, as most treatments are not clinically effective over placebo and most drugs have considerable side effects. On average, 75 % of the analgesic effect from OA treatments in clinical trials can be attributed to a placebo response, and this response varies greatly from patient to patient. This individual patient data (IPD) meta-analysis aims to identify placebo responders and the potential determinants of the placebo response in OA.

METHODS: This study is undertaken in conjunction with the OA Trial Bank, an ongoing international consortium aiming to collect IPD from randomised controlled trials (RCTs) for all treatments of OA. RCTs for each treatment of OA have been systematically searched for, and authors of the relevant trials have been contacted to request the IPD. We will use the IPD of placebo-controlled RCTs held by the OA Trial Bank for this project. The IPD in placebo groups will be used to investigate the placebo response according to the minimum clinically important difference (MCID) threshold (e.g. 20 % pain reduction). Responders to placebo will be compared with non-responders to identify predictors of response. The quality of the trials will be assessed and potential determinants will be examined using multilevel logistic regression analyses.

DISCUSSION: This study explores the varying magnitude of the placebo response and the proportion of participants that experience a clinically important placebo effect in OA RCTs. Potential determinants of the placebo response will also be investigated. These determinants may be useful for future studies as it may allow participants to be stratified into groups based on their likely response to placebo. The results of this study may also be useful for pharmaceutical companies, who could improve the design of their studies in order to separate the specific treatment from the non-specific contextual (i.e. placebo) effects.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016033212.
Fulltext Comparative efficacy of exercise therapy and oral non-steroidal anti-inflammatory drugs and paracetamol for knee or hip osteoarthritis: a network meta-analysis of randomised controlled trials

Weng Q, Goh SL, Wu J, Persson MSM, Wei J, Sarmanova A, et al.

Br J Sports Med, 2023 Aug;57(15):990-996.
PMID: 36593092 DOI: 10.1136/bjsports-2022-105898

OBJECTIVE: Clinical guidelines recommend exercise as a core treatment for knee or hip osteoarthritis (OA). However, how its analgesic effect compares to analgesics, for example, oral non-steroidal anti-inflammatory drugs (NSAIDs) and paracetamol-the most commonly used analgesics for OA, remains unknown.
DESIGN: Network meta-analysis.
DATA SOURCES: PubMed, Embase, Scopus, Cochrane Library and Web of Science from database inception to January 2022.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials (RCTs) comparing exercise therapy with oral NSAIDs and paracetamol directly or indirectly in knee or hip OA.
RESULTS: A total of n=152 RCTs (17 431 participants) were included. For pain relief, there was no difference between exercise and oral NSAIDs and paracetamol at or nearest to 4 (standardised mean difference (SMD)=-0.12, 95% credibility interval (CrI) -1.74 to 1.50; n=47 RCTs), 8 (SMD=0.22, 95% CrI -0.05 to 0.49; n=2 RCTs) and 24 weeks (SMD=0.17, 95% CrI -0.77 to 1.12; n=9 RCTs). Similarly, there was no difference between exercise and oral NSAIDs and paracetamol in functional improvement at or nearest to 4 (SMD=0.09, 95% CrI -1.69 to 1.85; n=40 RCTs), 8 (SMD=0.06, 95% CrI -0.20 to 0.33; n=2 RCTs) and 24 weeks (SMD=0.05, 95% CrI -1.15 to 1.24; n=9 RCTs).
CONCLUSIONS: Exercise has similar effects on pain and function to that of oral NSAIDs and paracetamol. Given its excellent safety profile, exercise should be given more prominence in clinical care, especially in older people with comorbidity or at higher risk of adverse events related to NSAIDs and paracetamol.CRD42019135166.
Drug allergy knowledge, attitude, and practice: A survey among doctors and pharmacists in public health facilities of Sabah, Malaysia

Kwan MSK, Tan SL, Keowmani T, Goh SL, Voo JYH, Tan HS, et al.

Asia Pac Allergy, 2023 Sep;13(3):121-126.
PMID: 37744958 DOI: 10.5415/apallergy.0000000000000115

BACKGROUND: Given the deficits in allergists and testing capacity, the diagnosis of drug allergy is largely dependent on the clinician's and pharmacist's judgment. The ability to recognize drug allergies and respond appropriately is crucial to patient safety. Currently, there is a void in the evidence that limits the ability to recommend comprehensive and swift improvements on this front.
OBJECTIVE: This study thus aimed to evaluate the knowledge, attitude, and practice toward drug allergy among doctors and pharmacists working in public healthcare facilities in Sabah, Malaysia.
METHODS: This cross-sectional study was conducted in 24 hospitals and 11 clinics in Sabah. A validated Drug Allergy Knowledge, Attitude, and Practice Questionnaire was adapted from a published study and developed on an online survey platform. The questionnaire was distributed to all listed eligible respondents via email and personal messenger service.
RESULTS: A total of 549 doctors and pharmacists responded, with an overall response rate of 18.2%. The total mean knowledge, attitude, and practice scores were 8.3 (SD, 1.98), 18.9 (SD, 2.55), and 17.3 (SD, 4.4), respectively. It was found that pharmacists performed significantly poorer than both medical officers (mean score difference = -0.5; P = 0.006) and specialists (mean score difference = -0.9; P = 0.020) in the knowledge domain. As the time in service doubles, the knowledge score increases significantly by 0.3 (P = 0.015).
CONCLUSION: Knowledge, attitude, and practice on drug allergy among doctors and pharmacists in Sabah were poor. It is thus timely for advanced educational programs on drug allergy to be formalized and implemented.
Fulltext Systematic comparison of plasma EBV DNA, anti-EBV antibodies and miRNA levels for early detection and prognosis of nasopharyngeal carcinoma

Tan LP, Tan GW, Sivanesan VM, Goh SL, Ng XJ, Lim CS, et al.

Int J Cancer, 2020 04 15;146(8):2336-2347.
PMID: 31469434 DOI: 10.1002/ijc.32656

Nasopharyngeal carcinoma (NPC) is originated from the epithelial cells of nasopharynx, Epstein-Barr virus (EBV)-associated and has the highest incidence and mortality rates in Southeast Asia. Late presentation is a common issue and early detection could be the key to reduce the disease burden. Sensitivity of plasma EBV DNA, an established NPC biomarker, for Stage I NPC is controversial. Most newly reported NPC biomarkers have neither been externally validated nor compared to the established ones. This causes difficulty in planning for cost-effective early detection strategies. Our study systematically evaluated six established and four new biomarkers in NPC cases, population controls and hospital controls. We showed that BamHI-W 76 bp remains the most sensitive plasma biomarker, with 96.7% (29/30), 96.7% (58/60) and 97.4% (226/232) sensitivity to detect Stage I, early stage and all NPC, respectively. Its specificity was 94.2% (113/120) against population controls and 90.4% (113/125) against hospital controls. Diagnostic accuracy of BamHI-W 121 bp and ebv-miR-BART7-3p were validated. Hsa-miR-29a-3p and hsa-miR-103a-3p were not, possibly due to lower number of advanced stage NPC cases included in this subset. Decision tree modeling suggested that combination of BamHI-W 76 bp and VCA IgA or EA IgG may increase the specificity or sensitivity to detect NPC. EBNA1 99 bp could identify NPC patients with poor prognosis in early and advanced stage NPC. Our findings provided evidence for improvement in NPC screening strategies, covering considerations of opportunistic screening, combining biomarkers to increase sensitivity or specificity and testing biomarkers from single sampled specimen to avoid logistic problems of resampling.