Statistical significance, clinical importance and effect sizes: Enhancing understanding of a study's results.

BACKGROUND: The proper interpretation of a study's results requires both excellent understanding of good methodological practices and deep knowledge of prior results, aided by the availability of effect sizes. METHODS: This review takes the form of an expository essay exploring the complex and nuanced relationships among statistical significance, clinical importance, and effect sizes. RESULTS: Careful attention to study design and methodology will increase the likelihood of obtaining statistical significance and may enhance the ability of investigators/readers to accurately interpret results. Measures of effect size show how well the variables used in a study account for/explain the variability in the data. Studies reporting strong effects may have greater practical value/utility than studies reporting weak effects. Effect sizes need to be interpreted in context. Verbal summary characterizations of effect sizes (e.g., "weak", "strong") are fundamentally flawed and can lead to inappropriate characterization of results. Common language effect size (CLES) indicators are a relatively new approach to effect sizes that may offer a more accessible interpretation of results that can benefit providers, patients, and the public at large. CONCLUSIONS: It is important to convey research findings in ways that are clear to both the research community and to the public. At a minimum, this requires inclusion of standard effect size data in research reports. Proper selection of measures and careful design of studies are foundational to the interpretation of a study's results. The ability to draw useful conclusions from a study is increased when investigators enhance the methodological quality of their work.

A Comprehensive Approach to PROMs in Elective Orthopedic Surgery: Comparing Effect Sizes across Patient Subgroups.

Background: There is limited knowledge regarding the comparative patient-reported outcomes (PROMs) and effect sizes (ESs) across orthopedic elective surgery. Methods: All patient data between January 2020 and December 2022 were collected, and treatment outcomes assessed as a PROM difference between baseline and one-year follow-up. The cohort was divided into subgroups (hand, elbow, shoulder, spine, hip, knee, and foot/ankle). The PROM ESs were calculated for each patient separately, and patients with ES > 0.5 were considered responders. Results: In total, 7695 patients were operated on. The mean ES across all patient groups was 1.81 (SD 1.41), and the largest ES was observed in shoulder patients and the smallest in hand patients. Overall, shoulder, hip, and knee patients had a larger ES compared to hand, spine, and foot/ankle patients (p < 0.0001). The proportion of positive responders ranged between 91-94% in the knee, shoulder, and hip, and 69-70% in the hand, spine, and foot/ankle subgroups. Conclusions: The ESs are generally high throughout elective orthopedic surgery. However, based on our institutional observations, shoulder, hip, and knee patients experience larger treatment effects compared to hand, spine, and foot/ankle patients, among whom there are also more non-responders. The expected treatment outcomes should be clearly communicated to patients when considering elective surgery. Because of the study limitations, the results should be approached with some caution.

Scaling and interpreting treatment effects in clinical trials using restricted mean survival time.

BACKGROUND: Restricted mean survival time is the expected duration of survival up to a chosen time of restriction τ. For comparison studies, the difference in restricted mean survival times between two groups provides a summary measure of the treatment effect that is free of assumptions regarding the relative shape of the two survival curves, such as proportional hazards. However, it can be difficult to judge the magnitude of the effect from a comparison of restricted means due to the truncation of observation at time τ. METHODS: In this article, we describe additional ways of expressing the treatment effect based on restricted means that can be helpful in this regard. These include the ratio of restricted means, the ratio of life-years (or time) lost, and the average integrated difference between the survival curves, equal to the difference in restricted means divided by τ. These alternative metrics are straightforward to calculate and provide a means for scaling the effect size as an aid to interpretation. Examples from two randomized, multicenter clinical trials in prostate cancer, NRG/RTOG 0521 and NRG/RTOG 0534, with primary endpoints of overall survival and biochemical/radiological progression-free survival, respectively, are presented to illustrate the ideas. RESULTS: The four effect measures (restricted mean survival time difference, restricted mean survival time ratio, time lost ratio, and average survival rate difference) were 0.45 years, 1.05, 0.81, and 0.038 for RTOG 0521 and 1.36 years, 1.17, 0.56, and 0.12 for RTOG 0534 with τ = 12 and 11 years, respectively. Thus, for example, the 0.45-year difference in the first trial translates into a 19% reduction in time lost and a 3.8% average absolute difference between the survival curves over the 12-year horizon, a modest effect size, whereas the 1.36-year difference in the second trial corresponds to a 44% reduction in time lost and a 12% absolute survival difference, a rather large effect. CONCLUSIONS: In addition to the difference in restricted mean survival times, these alternative measures can be helpful in determining whether the magnitude of the treatment effect is clinically meaningful.

Alternatives to the P value: connotations of significance.

The statistical significance of a clinical trial analysis result is determined by a mathematical calculation and probability based on null hypothesis significance testing. However, statistical significance does not always align with meaningful clinical effects; thus, assigning clinical relevance to statistical significance is unreasonable. A statistical result incorporating a clinically meaningful difference is a better approach to present statistical significance. Thus, the minimal clinically important difference (MCID), which requires integrating minimum clinically relevant changes from the early stages of research design, has been introduced. As a follow-up to the previous statistical round article on P values, confidence intervals, and effect sizes, in this article, we present hands-on examples of MCID and various effect sizes and discuss the terms statistical significance and clinical relevance, including cautions regarding their use.

Analysis of the Use of Sample Size and Effect Size Calculations in a Temporomandibular Disorders Randomised Controlled Trial-Short Narrative Review.

BACKGROUND/OBJECTIVES: Temporomandibular disorder (TMD) is the term used to describe a pathology (dysfunction and pain) in the masticatory muscles and temporomandibular joint (TMJ). There is an apparent upward trend in the publication of dental research and a need to continually improve the quality of research. Therefore, this study was conducted to analyse the use of sample size and effect size calculations in a TMD randomised controlled trial. METHODS: The period was restricted to the full 5 years, i.e., papers published in 2019, 2020, 2021, 2022, and 2023. The filter article type-"Randomized Controlled Trial" was used. The studies were graded on a two-level scale: 0-1. In the case of 1, sample size (SS) and effect size (ES) were calculated. RESULTS: In the entire study sample, SS was used in 58% of studies, while ES was used in 15% of studies. CONCLUSIONS: Quality should improve as research increases. One factor that influences quality is the level of statistics. SS and ES calculations provide a basis for understanding the results obtained by the authors. Access to formulas, online calculators and software facilitates these analyses. High-quality trials provide a solid foundation for medical progress, fostering the development of personalized therapies that provide more precise and effective treatment and increase patients' chances of recovery. Improving the quality of TMD research, and medical research in general, helps to increase public confidence in medical advances and raises the standard of patient care.

Meta-analysis of the association between gratitude and loneliness.

Gratitude is a positive social emotion that involves recognizing that others have brought benefits into one's life. Loneliness, on the other hand, is an unpleasant emotion resulting from a perceived lack of social connectedness. Although previous studies have reported an inverse association between gratitude and loneliness, these studies have not been systematically examined in a single review. To address this gap in the literature, we conducted a random-effects meta-analysis to examine the association between gratitude and loneliness. Analysis of 26 studies revealed a moderate sized effect (mean Fisher's z transformed correlation, zr = -.406, 95% confidence interval [CI] = -.463, -.349; mean back-transformed correlation, r = -.385, 95% CI = -.433, -.335). To complement these effect sizes, we calculated a probability-based common language effect size for correlations. Random-effects homogeneity testing suggested the presence of effect size heterogeneity. Analyses of both continuous and categorical moderators were non-significant, indicating that these variables did not influence effect size magnitude. Furthermore, publication bias tests suggested that our results were not influenced by unpublished studies. Finally, we proposed several statistical and clinical recommendations for future research. Regarding the latter, we offered suggestions for modifying gratitude enhancement programs with the aim of reducing loneliness.

Enhancing Medical Education through the "Distribute, Discuss, and Develop" Method: A Comparative Study of Small-Group Discussions.

Background Small-group discussions (SGDs) are pivotal in medical education, facilitating the development of critical thinking, communication skills, and teamwork. However, traditional SGDs face challenges such as scalability and maintaining student engagement. This study aims to evaluate the "Distribute, Discuss, and Develop" (3D) method for enhancing learning outcomes in medical education. Methods A single-blinded interventional study was conducted with 125 first-year Bachelor of Medicine and Bachelor of Surgery students, who were divided into intervention and control groups through random assignment. The intervention group employed the 3D method across two thematic units: hematology and muscle nerve physiology. The study assessed learning outcomes using pre- and posttests, class-average normalized gain ("g"), and feedback questionnaires to capture student perceptions of interaction, communication enhancement, and session summarization. Results The intervention group showed significantly improved learning outcomes in both thematic units, with larger effect sizes (hematology: 1.55; muscle nerve physiology: 1.4) compared to the control group. The normalized gain "g" indicated a medium effectiveness level for the intervention group in both themes, suggesting enhanced learning. Feedback questionnaires revealed higher satisfaction levels within the intervention group regarding interaction, communication skills, and session summarization. Conclusions The 3D method addresses the challenges faced by traditional SGDs, providing a scalable and engaging approach to medical education. By fostering more effective student-centered learning, the method enhances the comprehension of complex physiological concepts and improves communication skills. The 3D method significantly improves learning outcomes, interaction, and communication skills in medical education. This innovative approach to SGDs offers a promising strategy for enhancing the educational experience in medical schools, supporting the development of more articulate and professionally competent medical graduates.

Effect size varies based on calculation method and may affect interpretation of treatment effect: an illustration using randomised clinical trials in osteoarthritis.

BACKGROUND: To illustrate how (standardised) effect sizes (ES) vary based on calculation method and to provide considerations for improved reporting. METHODS: Data from three trials of tanezumab in subjects with osteoarthritis were analyzed. ES of tanezumab versus comparator for WOMAC Pain (outcome) was defined as least squares difference between means (mixed model for repeated measures analysis) divided by a pooled standard deviation (SD) of outcome scores. Three approaches to computing the SD were evaluated: Baseline (the pooled SD of WOMAC Pain values at baseline [pooled across treatments]); Endpoint (the pooled SD of these values at the time primary endpoints were assessed); and Median (the median pooled SD of these values based on the pooled SDs across available timepoints). Bootstrap analyses were used to compute 95% confidence intervals (CI). RESULTS: ES (95% CI) of tanezumab 2.5 mg based on Baseline, Endpoint, and Median SDs in one study were - 0.416 (- 0.796, - 0.060), - 0.195 (- 0.371, - 0.028), and - 0.196 (- 0.373, - 0.028), respectively; negative values indicate pain improvement. This pattern of ES differences (largest with Baseline SD, smallest with Endpoint SD, Median SD similar to Endpoint SD) was consistent across all studies and doses of tanezumab. CONCLUSION: Differences in ES affect interpretation of treatment effect. Therefore, we advocate clearly reporting individual elements of ES in addition to its overall calculation. This is particularly important when ES estimates are used to determine sample sizes for clinical trials, as larger ES will lead to smaller sample sizes and potentially underpowered studies. TRIAL REGISTRATION: Clinicaltrials.gov NCT02697773, NCT02709486, and NCT02528188.

On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries.

INTRODUCTION: Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. METHODS: We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. RESULTS: We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. DISCUSSION: We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.

Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing.

Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.

Combination therapy of Epidermal Growth Factor and Growth Hormone-Releasing Hexapeptide in acute ischemic stroke: a phase I/II non-blinded, randomized clinical trial.

Objective: This study tested the hypothesis that a neuroprotective combined therapy based on epidermal growth factor (EGF) and growth hormone-releasing hexapeptide (GHRP6) could be safe for acute ischemic stroke patients, admitting up to 30% of serious adverse events (SAE) with proven causality. Methods: A multi-centric, randomized, open-label, controlled, phase I-II clinical trial with parallel groups was conducted (July 2017 to January 2018). Patients aged 18-80 years with a computed tomography-confirmed ischemic stroke and less than 12 h from the onset of symptoms were randomly assigned to the study groups I (75 µg rEGF + 3.5 mg GHRP6 i.v., n=10), II (75 µg rEGF + 5 mg GHRP6 i.v., n=10), or III (standard care control, n=16). Combined therapy was given BID for 7 days. The primary endpoint was safety over 6 months. Secondary endpoints included neurological (NIHSS) and functional [Barthel index and modified Rankin scale (mRS)] outcomes. Results: The study population had a mean age of 66 ± 11 years, with 21 men (58.3%), a baseline median NIHSS score of 9 (95% CI: 8-11), and a mean time to treatment of 7.3 ± 2.8 h. Analyses were conducted on an intention-to-treat basis. SAEs were reported in 9 of 16 (56.2%) patients in the control group, 3 of 10 (30%) patients in Group I (odds ratio (OR): 0.33; 95% CI: 0.06-1.78), and 2 of 10 (20%) patients in Group II (OR: 0.19; 95% CI: 0.03-1.22); only two events in one patient in Group I were attributed to the intervention treatment. Compliance with the study hypothesis was greater than 0.90 in each group. Patients treated with EGF + GHRP6 had a favorable neurological and functional evolution at both 90 and 180 days, as evidenced by the inferential analysis of NIHSS, Barthel, and mRS and by their moderate to strong effect size. At 6 months, proportion analysis evidenced a higher survival rate for patients treated with the combined therapy. Ancillary analysis including merged treated groups and utility-weighted mRS also showed a benefit of this combined therapy. Conclusion: EGF + GHRP6 therapy was safe. The functional benefits of treatment in this study supported a Phase III study. Clinical Trial Registration: RPCEC00000214 of the Cuban Public Registry of Clinical Trials, Unique identifier: IG/CIGB-845I/IC/1601.

MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups.

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.

The impact of boarding school on student development in primary and secondary schools: a meta-analysis.

As a long-established model of schooling, the boarding system is commonly practiced in countries around the world. Numerous scholars have conducted a great deal of research on the relationship between the boarding school and student development, but the results of the research are quite divergent. In order to clarify the real effects of boarding school on students' development, this study used meta-analysis to quantify 49 (91 effect sizes) experimental or quasi-experimental studies on related topics at home and abroad. The results find that: (1) Overall, boarding school has no significant predictive effect on student development, with a combined effect size of 0.002 (p > 0.05); (2) Specifically, boarding school has a significant positive predictive effect on students' cognitive development (g = 0.248, p < 0.001), a significant negative predictive effect on students' affective and attitudinal development (g = -0.159, p < 0.05), and no significant predictive effect on students' behavioral development (g = -0.115, p > 0.05) and physical development (g = -0.038, p > 0.05); (3) The relationship between the two is moderated by the school stage and the type of boarding school, but not by the instruments; (4) Compared with primary school students, senior high school students and urban boarding students, the negative predictive effect of boarding system on junior middle school students and rural boarding students is more significant. In addition, there are some limitations in the study, such as the limited number of moderator variables included, the results of the study are easily affected by the quality of the included literature, and the dimensionality of the core variable "student development" is not comprehensive enough. In the future, further validation should be conducted through in-depth longitudinal or experimental studies.

Does nature-based social prescription improve mental health outcomes? A systematic review and meta-analysis.

Background: A nature-based social prescription (NBSP) is an approach to improving mental health outcomes that involves prescribing nature-based interventions as complementary or alternative therapy to traditional ones. A variety of advantages are available from NBSP for people looking to enhance their mental well-being. The effect size of the nature-based social prescriptions (NBSPs) has not been thoroughly evaluated by systematic reviews and meta-analyses. Objectives: The current study aimed to analyze existing studies and conduct a meta-analysis to determine the overall effect size of the nature-based social prescriptions (NBSP's) outcomes on mental health. Methods: By choosing the relevant papers from among those that were available, a meta-analysis was carried out in the current study. A systematic search of electronic databases (Pub Med, Web of Science, Scopus, Cochrane Library, Embase, CINAHL, and PsychINFO) was conducted to identify relevant studies. Studies were included if they evaluated the effects of NBSP on mental health outcomes. Effect sizes were calculated using the random effects model. Results: Meta-analysis of interventions statistics shows that CBT (SMD -0.0035; 95% CI: [-0.5090; 0.5020]; Tau^2: 0.1011; Tau: 0.318), digital intervention (SMD -0.3654; 95% CI: [-0.5258; 1.2566]; Tau^2: 0.2976, Tau: 0.5455), music intervention (SMD -2.1281; 95% CI: [-0.4659; 4.7221]; Tau^2: 3.4046; Tau:1.8452), and psychological interventions (SMD -0.8529; 95% CI: [0.3051; 1.4007]; Tau^2: 0.1224; Tau: 0.3499) do not significantly impact. The other interventions [social belongingness, communication training, blue intervention, nature-based education, cognitive behavior group therapy (CBGT), social prescribing coordinator, self-help intervention, participatory, organizational intervention, inpatient services, brief diet, internet-based intervention, prenatal intervention, yoga and meditation, ergonomics training program, yoga nidra intervention, and storytelling] highlighted above are significant. Conclusion: The conclusion of the meta-analysis supports the idea that incorporating nature-based social prescription interventions into mental healthcare plans can effectively complement traditional therapies and improve mental health outcomes. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023412458, CRD42023412458.

A Practical Significance Bias in Laypeople's Evaluation of Scientific Findings.

People often rely on scientific findings to help them make decisions-however, failing to report effect magnitudes might lead to a potential bias in assuming findings are practically significant. Across two online studies (Prolific; N = 800), we measured U.S. adults' endorsements of expensive interventions described in media reports that led to effects that were small, large, or of unreported magnitude between groups. Participants who viewed interventions with unreported effect magnitudes were more likely to endorse interventions compared with those who viewed interventions with small effects and were just as likely to endorse interventions as those who viewed interventions with large effects, suggesting a practical significance bias. When effect magnitudes were reported, participants on average adjusted their evaluations accordingly. However, some individuals, such as those with low numeracy skills, were more likely than others to act on small effects, even when explicitly prompted to first consider the meaningfulness of the effect.

What Threshold of Amyloid Reduction Is Necessary to Meaningfully Improve Cognitive Function in Transgenic Alzheimer's Disease Mice?

Background: Amyloid-ß plaques (Aß) are associated with Alzheimer's disease (AD). Pooled assessment of amyloid reduction in transgenic AD mice is critical for expediting anti-amyloid AD therapeutic research. Objective: The mean threshold of Aß reduction necessary to achieve cognitive improvement was measured via pooled assessment (n = 594 mice) of Morris water maze (MWM) escape latency of transgenic AD mice treated with substances intended to reduce Aß via reduction of beta-secretase cleaving enzyme (BACE). Methods: Machine learning and statistical methods identified necessary amyloid reduction levels using mouse data (e.g., APP/PS1, LPS, Tg2576, 3xTg-AD, control, wild type, treated, untreated) curated from 22 published studies. Results: K-means clustering identified 4 clusters that primarily corresponded with level of Aß: untreated transgenic AD control mice, wild type mice, and two clusters of transgenic AD mice treated with BACE inhibitors that had either an average 25% "medium reduction" of Aß or 50% "high reduction" of Aß compared to untreated control. A 25% Aß reduction achieved a 28% cognitive improvement, and a 50% Aß reduction resulted in a significant 32% improvement compared to untreated transgenic mice (p < 0.05). Comparatively, wild type mice had a mean 41% MWM latency improvement over untreated transgenic mice (p < 0.05). BACE reduction had a lesser impact on the ratio of Aß42 to Aß40. Supervised learning with an 80% -20% train-test split confirmed Aß reduction was a key feature for predicting MWM escape latency (R2 = 0.8 to 0.95). Conclusions: Results suggest a 25% reduction in Aß as a meaningful treatment threshold for improving transgenic AD mouse cognition.

The resilience of transplanted seagrass traits encourages detection of restoration success.

Restoration of coastal ecosystems, particularly those dominated by seagrasses, has become a priority to recover the important ecosystem services they provide. However, assessing restoration outcomes as a success or failure remains still difficult, probably due to the unique features of seagrass species and the wide portfolio of practices used on transplanting actions. Here, several traits (maximum leaf length, number of leaves, leaf growth rate per shoot, and leaf elemental carbon and nitrogen contents) of transplanted seagrass Posidonia oceanica were compared to reference meadows in five sites of Western Mediterranean Sea in which restoration were completed in different times. Results have evidenced the resilience of transplanted P. oceanica shoots within a few years since restoration, as traits between treatments changed depending on the elapsed time since settlement. The highlighted stability of the restoration time effect suggests that the recovery of the plants is expected in four years after transplanting.

A meta-analysis on the relationship between media with violence and aggression in Iranian sports.

The present research aimed to conduct a systematic study on violence and aggression in the context of Iranian sports and perform a meta-analysis to investigate the association between the media and violence and aggression in sports. The research encompassed all relevant studies available in scientific databases within Iran (such as Magiran, Seyed, Civilica, Normagz, Humane resource study, and police publications), as well as dissertations from the information and scientific documents database. The selected timeframe for this analysis covered the years 2001 to 2018 in the Iranian context. Through this process, 209 studies related to the subject were identified, out of which 10 studies were included in the meta-analysis based on the research protocol investigating the relationship between media and violence and aggression in sports. Data analysis was performed using SPSS25 and CMA2 software. The results showed several variables played prominent roles in the researches on violence and aggression in sports, including media performance, referees' performance, stadium amenities, law enforcement and security factors, external and internal stadium environment, coach's behavior, social control, family influence, education, socio-economic factors, substance abuse, players' behavior, influence of friends, managerial aspects, and cultural and political factors. Inferential statistics indicated effect size for the relationship between media and violence and aggression, under the fixed model, was determined to be 0.259, and under the random model, it was 0.306, both of which were statistically significant. Consequently, based on the findings from the meta-analysis, a significant direct relationship between media and violence and aggression in sports was established.

Effects of medical interventions on health-related quality of life in chronic disease - systematic review and meta-analysis of the 19 most common diagnoses.

Introduction: The demographic shift leads to a tremendous increase in age-related diseases, which are often chronic. Therefore, a focus of chronic disease management should be set on the maintenance or even improvement of the patients' quality of life (QoL). One indicator to objectively measure QoL is the EQ-5D questionnaire, which was validated in a disease- and world region-specific manner. The aim of this study was to conduct a systematic literature review and meta-analysis on the QoL across the most frequent chronic diseases that utilized the EQ-5D and performed a disease-specific meta-analysis for treatment-dependent QoL improvement. Materials and methods: The most common chronic disease in Germany were identified by their ICD-10 codes, followed by a systematic literature review of these ICD-10 codes and the EQ-5D index values. Finally, out of 10,016 independently -screened studies by two persons, 538 studies were included in the systematic review and 216 studies in the meta-analysis, respectively. Results: We found significant medium to large effect sizes of treatment effects, i.e., effect size >0.5, in musculoskeletal conditions with the exception of fractures, for chronic depression and for stroke. The effect size did not differ significantly from zero for breast and lung cancer and were significantly negative for fractures. Conclusion: Our analysis showed a large variation between baseline and post-treatment scores on the EQ-5D health index, depending on the health condition. We found large gains in health-related quality of life mainly for interventions for musculoskeletal disease. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020150936, PROSPERO identifier CRD42020150936.

Meta-Analysis of Studies on the Effects of Digital Therapeutics.

Digital therapeutics (DTx), novel treatment methods that have the potential to surpass traditional approaches such as pills, have received considerable research attention. Various efforts have been made to explore effective treatment methods that actively integrate DTx. This review investigates DTx treatment outcomes comprehensively through a meta-analysis. The analysis-a manual search of studies on "digital therapeutics"-includes DTx studies from January 2017 to October 2022. Hedges' g is used to quantify effect size for fifteen studies analyzed, encompassing eight control groups. Further, a quality assessment is performed using the Bias Risk Assessment Tool. The Hedges' g analysis results provide weighted average effect sizes across the eight control groups, revealing a substantial value of 0.91 (95% CI: 0.62 to 1.20); this signifies a moderate to large effect size. Further refinement, which excludes one study, yields an increased weighted average effect size of 1.13 (95% CI: 0.91 to 1.36). The quality assessment results consistently indicate a low risk of bias across studies. The meta-analysis results indicate that DTx can provide significant pivotal therapeutic impacts and offer a means to personalize treatment approaches and streamline the management of patients' treatment processes.