METHODS: This scoping review intended to investigate published studies on the current prevalence and incidence of oral cancer in LMICs. The review was conducted applying the search words "Oral Cancer" and "Mouth neoplasm" as the Medical Subject Heading (MeSH) major topic and "Epidemiology" and ("prevalence" OR "incidence") as the MeSH subheading; the search was supplemented by cross-references. Included studies met the following criteria: original studies, reporting of prevalence or incidence rates, population-based studies, studies in English language and studies involving humans.
RESULTS: The sample sizes ranged from 486 to 101,761 with 213,572 persons included. Buccal mucosa is one of the most common sites of oral cancer, associated with the widespread exposure to chewing tobacco. The incidence is likely to rise in the region where gutkha, pan masala, pan-tobacco and various other forms of chewing tobacco are popular.
CONCLUSION: This review contributes to useful information on prevalence and incidence estimates of oral cancer in LMICs.
METHODS: A cross-sectional, facility-based, concurrent mixed-methods study was carried out in seven health facilities in the Kailali, Baglung, and Ilam districts of Nepal. A total of 822 beneficiaries, sampled using probability proportional to size (PPS), attending health care institutions, were interviewed using a structured questionnaire for quantitative data. A total of seven focus group discussions (FGDs) and 12 in-depth interviews (IDIs), taken purposefully, were conducted with beneficiaries and service providers, using guidelines, respectively. Quantitative data were entered into Epi-data and analyzed with SPSS, MS-Excel, and Epitools, an online statistical calculator. Manual thematic analysis with predefined themes was carried out for qualitative data. Percentage, frequency, mean, and median were used to describe the variables, and the Chi-square test and binary logistic regression were used to infer the findings. We then combined the qualitative data from beneficiaries' and providers' perceptions, and experiences to explore different aspects of health insurance programs as well as to justify the quantitative findings.
RESULTS AND PROSPECTS: Of a total of 822 respondents (insured-404, uninsured-418), 370 (45%) were men. Families' median income was USD $65.96 (8.30-290.43). The perception of insurance premiums did not differ between the insured and uninsured groups (p = 0.53). Similarly, service utilization (OR = 220.4; 95% CI, 123.3-393.9) and accessibility (OR = 74.4; 95% CI, 42.5-130.6) were found to have high odds among the insured as compared to the uninsured respondents. Qualitative findings showed that the coverage and service quality were poor. Enrollment was gaining momentum despite nearly a one-tenth (9.1%) dropout rate. Moreover, different aspects, including provider-beneficiary communication, benefit packages, barriers, and ways to go, are discussed. Additionally, we also argue for some alternative health insurance schemes and strategies that may have possible implications in our contexts.
CONCLUSION: Although enrollment is encouraging, adherence is weak, with a considerable dropout rate and poor renewal. Patient management strategies and insurance education are recommended urgently. Furthermore, some alternate schemes and strategies may be considered.
OBJECTIVES: This study was devised to evaluate the health-related quality of life of people living with diabetes in Hail region of Saudi Arabia.
METHODS: This cross-sectional research was carried out at eight locations in the Hail region of Saudi Arabia between 21st March-20th May 2022 using the adapted version of the Euro QoL-5 dimension (EQ-5D-3L) questionnaire. A multistage random sample approach was used to choose the diabetes clinics, and data collectors approached the participants in the waiting areas to collect the information. The data were analyzed using logistic regression analysis, Mann-Whitney test, and Kruskal-Wallis tests in IBM SPSS statistics 21.0.
RESULTS: The mean HRQoL score was 0.71±0.21 with a visual analog score of 68.4±16.2. Despite having much higher levels of quality of life in terms of self-care (85.8%), regular activity (73.8%) and anxiety (71.8%), nearly one half of the people reported moderate pain or discomfort, and more than one third reported having moderate mobility issues. In general, the quality of life for women was poorer than for men. Individuals with diabetes who were unmarried, young, educated, financially secure, and taking only oral medication had much improved HRQoL. The Euro QoL of people with diabetes patients were significantly influenced by gender, marital status, age, education, employment and treatment modality (p-values < 0.05), whereas only treatment modality had a significant impact on the patients' visual analogue measures (p-values < 0.05).
CONCLUSIONS: The HRQoL of people with diabetes in Hail region was moderate in general, with pain and mobility issues being particularly prevalent. Gender, marital status, age, education, employment and type of medication therapy are significant predictors of HRQoL of patients with diabetes. Hence, planning and programs to enhance the HRQoL of people with diabetes, especially women is recommended.
METHODS: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores.
RESULTS: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)).
CONCLUSION: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.
OBJECTIVE: To evaluate the degree to which using data-driven methods to simultaneously select an optimal Patient Health Questionnaire-9 (PHQ-9) cutoff score and estimate accuracy yields (1) optimal cutoff scores that differ from the population-level optimal cutoff score and (2) biased accuracy estimates.
DESIGN, SETTING, AND PARTICIPANTS: This study used cross-sectional data from an existing individual participant data meta-analysis (IPDMA) database on PHQ-9 screening accuracy to represent a hypothetical population. Studies in the IPDMA database compared participant PHQ-9 scores with a major depression classification. From the IPDMA population, 1000 studies of 100, 200, 500, and 1000 participants each were resampled.
MAIN OUTCOMES AND MEASURES: For the full IPDMA population and each simulated study, an optimal cutoff score was selected by maximizing the Youden index. Accuracy estimates for optimal cutoff scores in simulated studies were compared with accuracy in the full population.
RESULTS: The IPDMA database included 100 primary studies with 44 503 participants (4541 [10%] cases of major depression). The population-level optimal cutoff score was 8 or higher. Optimal cutoff scores in simulated studies ranged from 2 or higher to 21 or higher in samples of 100 participants and 5 or higher to 11 or higher in samples of 1000 participants. The percentage of simulated studies that identified the true optimal cutoff score of 8 or higher was 17% for samples of 100 participants and 33% for samples of 1000 participants. Compared with estimates for a cutoff score of 8 or higher in the population, sensitivity was overestimated by 6.4 (95% CI, 5.7-7.1) percentage points in samples of 100 participants, 4.9 (95% CI, 4.3-5.5) percentage points in samples of 200 participants, 2.2 (95% CI, 1.8-2.6) percentage points in samples of 500 participants, and 1.8 (95% CI, 1.5-2.1) percentage points in samples of 1000 participants. Specificity was within 1 percentage point across sample sizes.
CONCLUSIONS AND RELEVANCE: This study of cross-sectional data found that optimal cutoff scores and accuracy estimates differed substantially from population values when data-driven methods were used to simultaneously identify an optimal cutoff score and estimate accuracy. Users of diagnostic accuracy evidence should evaluate studies of accuracy with caution and ensure that cutoff score recommendations are based on adequately powered research or well-conducted meta-analyses.