Tag: statistics

Mycoses. 2022 Aug 3. doi: 10.1111/myc.13511. Online ahead of print.

ABSTRACT

BACKGROUND: Malassezia folliculitis (MF) is a humid-favored fungal skin disease caused by Malassezia species. Inaccurate treatments, changes in skin flora, and disease exacerbation are often occurred due to oversights in the diagnosis. Several diagnostic methods are established for MF.

OBJECTIVE: To identify clinico-laboratory findings of Malassezia folliculitis in Indonesia.

METHODS: The study was conducted from January 2014 to December 2018 in seven referral teaching hospitals. Medical records of MF-diagnosed patients were obtained and analyzed using the binomial test, chi-square test, and Cohen’s Kappa coefficient in SPSS 26.0.

RESULTS: A total of 353 cases of MF were identified in seven referral teaching hospitals in Indonesia, 66.3% of which were males and 33.7% were females, dominated by the 17-25 years old group (44.5%). Itchy sensation (83.9%) was a major subjective complaint. Lesions were majorly found on the trunk-chest, back, and shoulder (68.3%), while the clinical manifestation are mostly follicular papule-pustular lesions (62.1%). Patients were 87.4% positive by KOH examination (modified Jacinto Jamora’s criteria) and 69.1% positive by Wood’s lamp. Generally, sex, age, subjective complaint, lesion location, clinical manifestation, and both examinations were statistically significant (p<0.001). A significant relationship between all the clinical criteria of the patients in the KOH; especially the clinical manifestation was significantly related to the Wood’s lamp. The Cohen’s Kappa assessment suggested that there was an agreement between KOH and Wood’s lamp (κ = -0,272, p<0.001).

CONCLUSION: The clinical symptoms of Malassezia folliculitis are dominated by pruritus, papulopustular follicular lesions on the trunk, and the presence of spore load.

PMID:35920036 | DOI:10.1111/myc.13511

Geriatr Gerontol Int. 2022 Aug 3. doi: 10.1111/ggi.14429. Online ahead of print.

ABSTRACT

AIM: To investigate the association between medication use and long-term all-cause mortality in a Brazilian stroke cohort.

METHODS: Both ischemic and hemorrhagic stroke were evaluated. Medication use was assessed as: never, only pre-stroke, only post-stroke, and continuous use. We evaluated anti-hypertensives, anti-diabetics, lipid-lowering drugs, anti-platelets, and anti-coagulants. Cox regression models were adjusted for sociodemographic and cardiovascular risk factors.

RESULTS: Among 1173 incident stroke cases (median age: 68; 86.8% were ischemic, 70% first-ever stroke), medication use was low (overall: 17.5% pre-stroke, 26.4% post-stroke, and 40% were under continuous use). Anti-hypertensives and anti-platelets (aspirin) were the continuous cardiovascular medications used most often, at 83.5% and 72%, respectively, while statins (39.7%) and anti-diabetics (31.3%) were the least used. Medication use (pre-stroke, post-stroke and continuous use) was associated with a reduction in all-cause mortality risk, particularly among those under continuous use (multivariable hazard ratio, 0.52; 95% confidence interval (CI), 0.46-0.66) compared with never-users. Among ischemic stroke patients, this effect was similar (multivariable hazard ratio, 0.52; 95% CI, 0.40-0.68). No significant associations were evident among hemorrhagic stroke patients.

CONCLUSIONS: The risk of all-cause mortality was reduced by 48% among those with ischemic stroke under continuous use of medications. Secondary prevention should be emphasized more strongly in clinical practice. Geriatr Gerontol Int 2022; ••: ••-••.

PMID:35920018 | DOI:10.1111/ggi.14429

Cancer Res. 2022 Aug 3;82(15):2674-2677. doi: 10.1158/0008-5472.CAN-21-2978.

ABSTRACT

In recent years, there has been a growing recognition that P values, albeit useful in reporting data analysis results, have often been misused or misinterpreted in biomedical research. The emergence of big health data such as genomics data and electronic health records, sometimes combined with inadequate experimental design, has exacerbated this problem, which has become a major cause of the ongoing crisis in reproducibility in biomedical research. We aim to shed light and raise awareness of common misuses and pitfalls of P values and discuss potential mitigation strategies that leverage state-of-the-art statistical methods. The best practices always start with a sound study design including a robust data collection strategy to minimize data bias and a carefully thought-out analysis plan that can address potential misuses and pitfalls of P values. We highly encourage biomedical researchers to engage and involve statisticians from the very beginning of their studies.

PMID:35919988 | DOI:10.1158/0008-5472.CAN-21-2978

J R Soc Interface. 2022 Aug;19(193):20220123. doi: 10.1098/rsif.2022.0123. Epub 2022 Aug 3.

ABSTRACT

Timely forecasts of the emergence, re-emergence and elimination of human infectious diseases allow for proactive, rather than reactive, decisions that save lives. Recent theory suggests that a generic feature of dynamical systems approaching a tipping point-early warning signals (EWS) due to critical slowing down (CSD)-can anticipate disease emergence and elimination. Empirical studies documenting CSD in observed disease dynamics are scarce, but such demonstration of concept is essential to the further development of model-independent outbreak detection systems. Here, we use fitted, mechanistic models of measles transmission in four cities in Niger to detect CSD through statistical EWS. We find that several EWS accurately anticipate measles re-emergence and elimination, suggesting that CSD should be detectable before disease transmission systems cross key tipping points. These findings support the idea that statistical signals based on CSD, coupled with decision-support algorithms and expert judgement, could provide the basis for early warning systems of disease outbreaks.

PMID:35919978 | DOI:10.1098/rsif.2022.0123

Eur J Prev Cardiol. 2022 Aug 3:zwac148. doi: 10.1093/eurjpc/zwac148. Online ahead of print.

ABSTRACT

BACKGROUND: There are several risk scores designed to predict mortality in patients with heart failure (HF).

AIM: To assess performance of risk scores validated for mortality prediction in patients with acute HF (AHF) and chronic HF.

METHODS: MEDLINE and Scopus were searched from January 2015 to January 2021 for studies which internally or externally validated risk models for predicting all-cause mortality in patients with AHF and chronic HF. Discrimination data were analyzed using C-statistics, and pooled using generic inverse-variance random-effects model.

RESULTS: Nineteen studies (n = 494,156 patients; AHF:24,762; chronic HF mid-term mortality:62,000; chronic HF long-term mortality:452,097) and 11 risk scores were included. Overall, discrimination of risk scores was good across the three subgroups: AHF mortality (C-statistic:0.76, [0.68-0.83]), chronic HF mid-term mortality (1 year; C-statistic:0.74, [0.68-0.79]) and chronic HF long-term mortality (≥2 years; C-statistic:0.71, [0.69-0.73]). MEESSI-AHF (C-statistic:0.81, [0.80-0.83]) and MARKER-HF (C-statistic:0.85, [0.80-0.89]) had excellent discrimination for AHF and chronic HF mid-term mortality respectively, whereas MECKI had good discrimination (C-statistic:0.78, [0.73-0.83]) for chronic HF long-term mortality relative to other models. Overall, risk scores predicting short-term mortality in patients with AHF did not have evidence of poor calibration (Hosmer-Lemeshow p > 0.05). However, risk models predicting mid-term and long-term mortality in patients with chronic HF varied in calibration performance.

CONCLUSIONS: Majority of recently validated risk scores showed good discrimination for mortality in patients with HF. MEESSI-AHF demonstrated excellent discrimination in patients with AHF, and MARKER-HF and MECKI displayed excellent discrimination in patients with chronic HF. However, modest reporting of calibration and lack of head-to-head comparisons in same populations warrant future studies.

PMID:35919956 | DOI:10.1093/eurjpc/zwac148

Ann Pharmacother. 2022 Aug 2:10600280221113092. doi: 10.1177/10600280221113092. Online ahead of print.

ABSTRACT

OBJECTIVES: To review the characteristics, efficacy, safety, pharmacoeconomics, and place in therapy of upadacitinib, a Janus kinase (JAK) inhibitor, in the treatment of rheumatoid arthritis (RA).

DATA SOURCES: PubMed (January 2003-May 2022) was searched using upadacitinib and ABT-494.

STUDY SELECTION AND DATA EXTRACTION: Human studies published in peer-reviewed publications in English were the primary sources for efficacy and safety data.

DATA SYNTHESIS: In randomized, double-blind, controlled clinical studies, upadacitinib demonstrated statistically significant improvement in RA symptoms as monotherapy and in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) when compared with csDMARD monotherapy or to adalimumab or abatacept in combination with csDMARD therapy in patients with RA. American College of Rheumatology 20% response rates were 68% to 79% for upadacitinib monotherapy and 64% to 84% for upadacitinib plus csDMARD therapy, compared with 28% to 59% for csDMARD-only therapy and 63% to 74% for biologic DMARD (bDMARD) plus csDMARD therapy. Long-term extension studies demonstrated similar findings. Upadacitinib had similar rates of serious infections, herpes zoster, major cardiovascular events, and venous thromboembolic events as other JAK inhibitors. Upadacitinib was similar in cost to tofacitinib and twice as high as baricitinib based on current estimated costs to patients, but actual costs may vary.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: Upadacitinib is an alternative therapy to other JAK inhibitors and bDMARDs in patients with moderate to severe RA who have had an inadequate response to a tumor necrosis factor inhibitor alone or in combination with a csDMARD.

CONCLUSIONS: Upadacitinib is an effective JAK inhibitor for use in RA.

PMID:35919945 | DOI:10.1177/10600280221113092

Mod Rheumatol. 2022 Aug 3:roac079. doi: 10.1093/mr/roac079. Online ahead of print.

ABSTRACT

OBJECTIVES: To elucidate the longitudinal relationship between bone mineral density (BMD) at baseline and the change of bone marrow lesion (BML) during a two-year follow-up period (2YFU).

METHODS: Seventy-eight female participants (Mean age: 54.9 ± 9.6) without radiographic knee osteoarthritis were eligible. Based on right-knee MRI, maximum BML area (BMLa) was calculated by tracing BML border. The change in BMLa was defined using the following formula: [2YFU] – [Baseline] = ΔBMLa. Positive ΔBMLa was defined as enlarged; negative ΔBMLa was defined as regressed. Dual-energy X-ray absorptiometry was performed to measure the BMD of distal radius. Young adult mean [YAM (%)] of the BMD was used for statistical analysis. Linear regression analysis was conducted with ΔBMLa as the dependent variable and YAM as the independent variable. ROC curve and logistic regression analysis were conducted for YAM to predict the prevalence of BML enlargement or regression.

RESULTS: Twenty-six (33.3%) patients had enlarged BMLa, 12 (15.4%) participants showed regressing BMLa, and 40 (51.3%) patients remained stable. YAM was negatively associated with ΔBMLa (β: – 0.375, P=0.046). The best predictor of BML enlargement risk was 85% YAM; this cut-off could predict the prevalence of BML enlargement (Odds ratio: 8.383, P=0.025).

CONCLUSIONS: Lower BMD could predict BML enlargement during a two-year follow-up period.

PMID:35919930 | DOI:10.1093/mr/roac079

J Evid Based Med. 2022 Aug 2. doi: 10.1111/jebm.12484. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the reporting quality of single-patient (N-of-1) trials and protocols based on the CONSORT Extension for N-of-1 trials (CENT) statement and the standard protocol items: recommendations for interventional trials (SPIRIT) extension and elaboration for N-of-1 trials (SPENT) checklist to examine the factors that influenced reporting quality.

METHODS: Four electronic databases were searched to identify N-of-1 trials and protocols from 2015 to 2020. Quality was assessed by two reviewers. We calculated the overall scores based on binary responses in which “Yes” was scored as 1 (if the item was fully reported), and “No” was scored as 0 (if the item was not clearly reported or not definitely stated).

RESULTS: A total of 78 publications (55 N-of-1 trials and 23 protocols) were identified. The mean reporting score (SD) of the N-of-1 trials and protocols were 29.24 (0.89) and 29.61 (1.83), respectively. For the items related to outcomes, sample size, allocation concealment protocol, and informed consent materials, the reporting quality was low. Our results showed that the year of publication (t = -0.793, p = 0.872 for the trials and t = 1.352, p = 0.623 for the protocols) and the impact factor of the journal (t = 1.416, p = 0.619 for the trials and t = 0.359, p = 0.667 for the protocols) were not factors associated with better reporting quality.

CONCLUSION: With the publication of the CENT 2015 statement and the SPENT 2019 checklist, authors should adhere to the relevant reporting guidelines and improve the reporting quality of N-of-1 trials and protocols.

PMID:35919928 | DOI:10.1111/jebm.12484

Geriatr Gerontol Int. 2022 Aug 2. doi: 10.1111/ggi.14435. Online ahead of print.

ABSTRACT

AIM: To investigate the association between the total score of the Kihon checklist (t-KCL score) and functional disability over an 8-year follow-up period, and to examine whether the t-KCL score in the basic model with risk factors contributes to the incremental predictive ability for functional disability among older adults.

METHODS: We followed 2209 older adults aged ≥65 years without functional disability at baseline. The t-KCL score was determined using a baseline survey questionnaire. Functional disability was defined based on information from long-term care certifications. The association between the t-KCL score and functional disability was examined using the Cox proportional hazards model. The incremental predictive ability of the t-KCL score for functional disability was evaluated by the difference of the C-statistic, category-free net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS: The median follow-up period was 7.8 years, and 557 participants developed functional disability. The adjusted hazard ratio (95% confidence interval [CI]) of functional disability for a 1-point increase of the t-KCL score was 1.08 (1.06-1.10). Adding the t-KCL score to the basic model significantly improved the C-statistic (95% CI) from 0.747 (0.728-0.768) to 0.760 (0.741-0.781). When the t-KCL score was added to the basic model, the NRI and IDI were 0.187 (95% CI: 0.095-0.287) and 0.020 (95% CI: 0.012-0.027), respectively.

CONCLUSIONS: The t-KCL score had an independent positive association with functional disability over an 8-year follow-up. Furthermore, adding the t-KCL score to the basic model improved the predictive ability for functional disability. Geriatr Gerontol Int 2022; ••: ••-••.

PMID:35919927 | DOI:10.1111/ggi.14435

J Osteopath Med. 2022 Aug 2. doi: 10.1515/jom-2021-0296. Online ahead of print.

ABSTRACT

CONTEXT: Health-related quality of life (HRQOL) represents a new approach for guiding chronic pain management because it is patient-centered and more likely to be understood and accepted by patients.

OBJECTIVES: To assess the value and utility of an eHealth intervention for patients with chronic low back pain (CLBP) that was primarily based on HRQOL measures and to measure the clinical outcomes associated with its use.

METHODS: A randomized controlled trial was conducted within the Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation (PRECISION Pain Research Registry) using participants screened from November 2019 through February 2021. A total of 331 registry participants within the 48 contiguous states and the District of Columbia met the eligibility criteria, which included having CLBP and HRQOL deficits. Almost three-fourths of the participants were enrolled after onset of the COVID-19 pandemic. The participants were randomized to an eHealth intervention for HRQOL or wait list control. The primary outcome measures involved HRQOL based on the Patient-Reported Outcomes Measurement Information System (PROMIS), including the SPADE cluster (Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue) and each of its five component scales. Secondary outcome measures involved low back pain intensity and back-related functioning. Changes over time for each outcome measure reported by participants in each treatment group were compared utilizing the student’s t-test for statistical significance and Cohen’s d statistic for clinical importance. Outcomes were reported as between-group differences in change scores and the d statistic, with positive values favoring the experimental treatment group.

RESULTS: There were no significant differences between the experimental and control treatment groups for changes over time in any primary outcome measure. The d statistic (95% confidence interval) for the difference between the experimental and control treatment groups on the SPADE cluster was 0.04 (-0.18-0.25). The corresponding d statistics for the SPADE scales ranged from -0.06 (-0.27 to 0.16) for anxiety to 0.11 (-0.10 to 0.33) for sleep disturbance. There were also no significant or clinically important differences between the experimental and control treatment groups on the secondary outcome measures. Additionally, in subgroup analyses involving participants treated by osteopathic vs allopathic physicians, no significant interaction effects were observed.

CONCLUSIONS: The eHealth intervention studied herein did not achieve statistically significant or clinically important improvements in any of the primary or secondary outcome measures. However, the validity and generalizability of the findings may have been limited by the unforeseen onset and impact of the COVID-19 pandemic shortly after beginning the trial.

PMID:35918787 | DOI:10.1515/jom-2021-0296