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  1. Shrestha AD, Vedsted P, Kallestrup P, Neupane D
    Eur J Cancer Care (Engl), 2020 Mar;29(2):e13207.
    PMID: 31820851 DOI: 10.1111/ecc.13207
    INTRODUCTION: Oral cancer is common cancer in many low- and middle-income countries (LMICs) with a low five-year survival rate. It is among the four most common types of cancer in South East Asia region. In South-Central Asia, lip and oral cavity cancer is the second most common cancer according to the specific cancer types.

    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.

  2. Paneru DP, Adhikari C, Poudel S, Adhikari LM, Neupane D, Bajracharya J, et al.
    Front Public Health, 2022;10:978732.
    PMID: 36589957 DOI: 10.3389/fpubh.2022.978732
    OBJECTIVE: The Social Health Insurance Program (SHIP) shares a major portion of social security, and is also key to Universal Health Coverage (UHC) and health equity. The Government of Nepal launched SHIP in the Fiscal Year 2015/16 for the first phase in three districts, on the principle of financial risk protection through prepayment and risk pooling in health care. Furthermore, the adoption of the program depends on the stakeholders' behaviors, mainly, the beneficiaries and the providers. Therefore, we aimed to explore and assess their perception and experiences regarding various factors acting on SHIP enrollment and adherence.

    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.

  3. Alshammari F, Ansari M, Khan KU, Neupane D, Hussain A, Anwar S, et al.
    PLoS One, 2024;19(5):e0299995.
    PMID: 38713663 DOI: 10.1371/journal.pone.0299995
    BACKGROUND: Diabetes Mellitus is a serious and expanding health problem, together with the issues of health- related quality of life (HRQoL). This further puts pressure on the government to allocate more funds for public healthcare.

    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.

  4. Davidar P, Sharma R, de Silva S, Campos-Arceiz A, Goossens B, Puyravaud JP, et al.
    Science, 2023 Feb 24;379(6634):765.
    PMID: 36821683 DOI: 10.1126/science.adg7470
  5. Schutte AE, Jafar TH, Poulter NR, Damasceno A, Khan NA, Nilsson PM, et al.
    Cardiovasc Res, 2023 Mar 31;119(2):381-409.
    PMID: 36219457 DOI: 10.1093/cvr/cvac130
    Raised blood pressure (BP) is the leading cause of preventable death in the world. Yet, its global prevalence is increasing, and it remains poorly detected, treated, and controlled in both high- and low-resource settings. From the perspective of members of the International Society of Hypertension based in all regions, we reflect on the past, present, and future of hypertension care, highlighting key challenges and opportunities, which are often region-specific. We report that most countries failed to show sufficient improvements in BP control rates over the past three decades, with greater improvements mainly seen in some high-income countries, also reflected in substantial reductions in the burden of cardiovascular disease and deaths. Globally, there are significant inequities and disparities based on resources, sociodemographic environment, and race with subsequent disproportionate hypertension-related outcomes. Additional unique challenges in specific regions include conflict, wars, migration, unemployment, rapid urbanization, extremely limited funding, pollution, COVID-19-related restrictions and inequalities, obesity, and excessive salt and alcohol intake. Immediate action is needed to address suboptimal hypertension care and related disparities on a global scale. We propose a Global Hypertension Care Taskforce including multiple stakeholders and societies to identify and implement actions in reducing inequities, addressing social, commercial, and environmental determinants, and strengthening health systems implement a well-designed customized quality-of-care improvement framework.
  6. Charchar FJ, Prestes PR, Mills C, Ching SM, Neupane D, Marques FZ, et al.
    J Hypertens, 2024 Jan 01;42(1):23-49.
    PMID: 37712135 DOI: 10.1097/HJH.0000000000003563
    Hypertension, defined as persistently elevated systolic blood pressure (SBP) >140 mmHg and/or diastolic blood pressure (DBP) at least 90 mmHg (International Society of Hypertension guidelines), affects over 1.5 billion people worldwide. Hypertension is associated with increased risk of cardiovascular disease (CVD) events (e.g. coronary heart disease, heart failure and stroke) and death. An international panel of experts convened by the International Society of Hypertension College of Experts compiled lifestyle management recommendations as first-line strategy to prevent and control hypertension in adulthood. We also recommend that lifestyle changes be continued even when blood pressure-lowering medications are prescribed. Specific recommendations based on literature evidence are summarized with advice to start these measures early in life, including maintaining a healthy body weight, increased levels of different types of physical activity, healthy eating and drinking, avoidance and cessation of smoking and alcohol use, management of stress and sleep levels. We also discuss the relevance of specific approaches including consumption of sodium, potassium, sugar, fibre, coffee, tea, intermittent fasting as well as integrated strategies to implement these recommendations using, for example, behaviour change-related technologies and digital tools.
  7. Wu Y, Levis B, Daray FM, Ioannidis JPA, Patten SB, Cuijpers P, et al.
    Psychol Assess, 2023 Feb;35(2):95-114.
    PMID: 36689386 DOI: 10.1037/pas0001181
    The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from -0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02-0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
  8. Wu Y, Levis B, Sun Y, Krishnan A, He C, Riehm KE, et al.
    J Psychosom Res, 2020 02;129:109892.
    PMID: 31911325 DOI: 10.1016/j.jpsychores.2019.109892
    OBJECTIVE: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D).

    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.

  9. Levis B, Bhandari PM, Neupane D, Fan S, Sun Y, He C, et al.
    JAMA Netw Open, 2024 Nov 04;7(11):e2429630.
    PMID: 39576645 DOI: 10.1001/jamanetworkopen.2024.29630
    IMPORTANCE: Test accuracy studies often use small datasets to simultaneously select an optimal cutoff score that maximizes test accuracy and generate accuracy estimates.

    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.

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