Tag: statistics

JMIR Infodemiology. 2024 Mar 19;4:e51113. doi: 10.2196/51113.

ABSTRACT

BACKGROUND: The COVID-19 pandemic triggered unprecedented global vaccination efforts, with social media being a popular tool for vaccine promotion.

OBJECTIVE: This study probes into Macao’s COVID-19 vaccine communication dynamics, with a focus on the multifaceted impacts of government agendas on social media.

METHODS: We scrutinized 22,986 vaccine-related Facebook posts from January 2020 to August 2022 in Macao. Using automated content analysis and advanced statistical methods, we unveiled intricate agenda dynamics between government and nongovernment entities.

RESULTS: “Vaccine importance” and “COVID-19 risk” were the most prominent topics co-occurring in the overall vaccine communication. The government tended to emphasize “COVID-19 risk” and “vaccine effectiveness,” while regular users prioritized vaccine safety and distribution, indicating a discrepancy in these agendas. Nonetheless, the government has limited impact on regular users in the aspects of vaccine importance, accessibility, affordability, and trust in experts. The agendas of government and nongovernment users intertwined, illustrating complex interactions.

CONCLUSIONS: This study reveals the influence of government agendas on public discourse, impacting environmental awareness, public health education, and the social dynamics of inclusive communication during health crises. Inclusive strategies, accommodating public concerns, and involving diverse stakeholders are paramount for effective social media communication during health crises.

PMID:38502184 | DOI:10.2196/51113

JMIR Public Health Surveill. 2024 Mar 19;10:e48738. doi: 10.2196/48738.

ABSTRACT

BACKGROUND: Population size, prevalence, and incidence are essential metrics that influence public health programming and policy. However, stakeholders are frequently tasked with setting performance targets, reporting global indicators, and designing policies based on multiple (often incongruous) estimates of these variables, and they often do so in the absence of a formal, transparent framework for reaching a consensus estimate.

OBJECTIVE: This study aims to describe a model to synthesize multiple study estimates while incorporating stakeholder knowledge, introduce an R Shiny app to implement the model, and demonstrate the model and app using real data.

METHODS: In this study, we developed a Bayesian hierarchical model to synthesize multiple study estimates that allow the user to incorporate the quality of each estimate as a confidence score. The model was implemented as a user-friendly R Shiny app aimed at practitioners of population size estimation. The underlying Bayesian model was programmed in Stan for efficient sampling and computation.

RESULTS: The app was demonstrated using biobehavioral survey-based population size estimates (and accompanying confidence scores) of female sex workers and men who have sex with men from 3 survey locations in a country in sub-Saharan Africa. The consensus results incorporating confidence scores are compared with the case where they are absent, and the results with confidence scores are shown to perform better according to an app-supplied metric for unaccounted-for variation.

CONCLUSIONS: The utility of the triangulator model, including the incorporation of confidence scores, as a user-friendly app is demonstrated using a use case example. Our results offer empirical evidence of the model’s effectiveness in producing an accurate consensus estimate and emphasize the significant impact that the accessible model and app offer for public health. It offers a solution to the long-standing problem of synthesizing multiple estimates, potentially leading to more informed and evidence-based decision-making processes. The Triangulator has broad utility and flexibility to be adapted and used in various other contexts and regions to address similar challenges.

PMID:38502183 | DOI:10.2196/48738

JMIR Cancer. 2024 Mar 19;10:e52322. doi: 10.2196/52322.

ABSTRACT

BACKGROUND: People with cancer frequently experience severe and distressing symptoms associated with cancer and its treatments. Predicting symptoms in patients with cancer continues to be a significant challenge for both clinicians and researchers. The rapid evolution of machine learning (ML) highlights the need for a current systematic review to improve cancer symptom prediction.

OBJECTIVE: This systematic review aims to synthesize the literature that has used ML algorithms to predict the development of cancer symptoms and to identify the predictors of these symptoms. This is essential for integrating new developments and identifying gaps in existing literature.

METHODS: We conducted this systematic review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. We conducted a systematic search of CINAHL, Embase, and PubMed for English records published from 1984 to August 11, 2023, using the following search terms: cancer, neoplasm, specific symptoms, neural networks, machine learning, specific algorithm names, and deep learning. All records that met the eligibility criteria were individually reviewed by 2 coauthors, and key findings were extracted and synthesized. We focused on studies using ML algorithms to predict cancer symptoms, excluding nonhuman research, technical reports, reviews, book chapters, conference proceedings, and inaccessible full texts.

RESULTS: A total of 42 studies were included, the majority of which were published after 2017. Most studies were conducted in North America (18/42, 43%) and Asia (16/42, 38%). The sample sizes in most studies (27/42, 64%) typically ranged from 100 to 1000 participants. The most prevalent category of algorithms was supervised ML, accounting for 39 (93%) of the 42 studies. Each of the methods-deep learning, ensemble classifiers, and unsupervised ML-constituted 3 (3%) of the 42 studies. The ML algorithms with the best performance were logistic regression (9/42, 17%), random forest (7/42, 13%), artificial neural networks (5/42, 9%), and decision trees (5/42, 9%). The most commonly included primary cancer sites were the head and neck (9/42, 22%) and breast (8/42, 19%), with 17 (41%) of the 42 studies not specifying the site. The most frequently studied symptoms were xerostomia (9/42, 14%), depression (8/42, 13%), pain (8/42, 13%), and fatigue (6/42, 10%). The significant predictors were age, gender, treatment type, treatment number, cancer site, cancer stage, chemotherapy, radiotherapy, chronic diseases, comorbidities, physical factors, and psychological factors.

CONCLUSIONS: This review outlines the algorithms used for predicting symptoms in individuals with cancer. Given the diversity of symptoms people with cancer experience, analytic approaches that can handle complex and nonlinear relationships are critical. This knowledge can pave the way for crafting algorithms tailored to a specific symptom. In addition, to improve prediction precision, future research should compare cutting-edge ML strategies such as deep learning and ensemble methods with traditional statistical models.

PMID:38502171 | DOI:10.2196/52322

Rev Neurol. 2024 Apr 1;78(7):209-211. doi: 10.33588/rn.7807.2023164.

ABSTRACT

Leading scientific journals in fields such as medicine, biology and sociology repeatedly publish articles and editorials claiming that a large percentage of doctors do not understand the basics of statistical analysis, which increases the risk of errors in interpreting data, makes them more vulnerable to misinformation and reduces the effectiveness of research. This problem extends throughout their careers and is largely due to the poor training they receive in statistics – a problem that is common in developed countries. As stated by H. Halle and S. Krauss, ‘90% of German university lecturers who regularly use the p-value in tests do not understand what that value actually measures’. It is important to note that the basic reasoning of statistical analysis is similar to what we do in our daily lives and that understanding the basic concepts of statistical analysis does not require any knowledge of mathematics. Contrary to what many researchers believe, the p-value of the test is not a ‘mathematical index’ that allows us to clearly conclude whether, for example, a drug is more effective than a placebo. The p-value of the test is simply a percentage.

PMID:38502169 | DOI:10.33588/rn.7807.2023164

JMIR Form Res. 2024 Mar 19;8:e55041. doi: 10.2196/55041.

ABSTRACT

BACKGROUND: Alcohol misuse is the fourth leading cause of death in the United States and a significant problem in the US military. Brief alcohol interventions can reduce negative alcohol outcomes in civilian and military populations, but additional scalable interventions are needed to reduce binge and heavy drinking. SMS text messaging interventions could address this need, but to date, no programs exist for military populations.

OBJECTIVE: We aimed to develop an SMS text messaging intervention to address binge and heavy drinking among Airmen in Technical Training in the US Air Force.

METHODS: We implemented a 2-phase, mixed methods study to develop the SMS text messaging intervention. In phase 1, a total of 149 respondents provided feedback about the persuasiveness of 49 expert-developed messages, preferences regarding message frequency, timing and days to receive messages, and suggested messages, which were qualitatively coded. In phase 2, a total of 283 respondents provided feedback about the persuasiveness of 77 new messages, including those developed through the refinement of messages from phase 1, which were coded and assessed based on the Behavior Change Technique Taxonomy (BCTT). For both phases, mean persuasiveness scores (range 1-5) were calculated and compared according to age (aged <21 or ≥21 years) and gender. Top-ranking messages from phase 2 were considered for inclusion in the final message library.

RESULTS: In phase 1, top-rated message themes were about warnings about adverse outcomes (eg, impaired judgment and financial costs), recommendations to reduce drinking, and invoking values and goals. Through qualitative coding of suggested messages, we identified themes related to warnings about adverse outcomes, recommendations, prioritizing long-term goals, team and belonging, and invoking values and goals. Respondents preferred to receive 1 to 3 messages per week (124/137, 90.5%) and to be sent messages on Friday, Saturday, and Sunday (65/142, 45.8%). In phase 2, mean scores for messages in the final message library ranged from 3.31 (SD 1.29) to 4.21 (SD 0.90). Of the top 5 highest-rated messages, 4 were categorized into 2 behavior change techniques (BCTs): valued self-identity and information about health consequences. The final message library includes 28 BCTT-informed messages across 13 BCTs, with messages having similar scores across genders. More than one-fourth (8/28, 29%) of the final messages were informed by the suggested messages from phase 1. As Airmen aged <21 years face harsher disciplinary action for alcohol consumption, the program is tailored based on the US legal drinking age.

CONCLUSIONS: This study involved members from the target population throughout 2 formative stages of intervention development to design a BCTT-informed SMS text messaging intervention to reduce binge and heavy drinking, which is now being tested in an efficacy trial. The results will determine the impact of the intervention on binge drinking and alcohol consumption in the US Air Force.

PMID:38502165 | DOI:10.2196/55041

JAMA Netw Open. 2024 Mar 4;7(3):e242366. doi: 10.1001/jamanetworkopen.2024.2366.

ABSTRACT

IMPORTANCE: Minor head trauma (HT) is one of the most common causes of hospitalization in children. A diagnostic test could prevent unnecessary hospitalizations and cranial computed tomographic (CCT) scans.

OBJECTIVE: To evaluate the effectiveness of serum S100B values in reducing exposure to CCT scans and in-hospital observation in children with minor HT.

DESIGN, SETTING, AND PARTICIPANTS: This multicenter, unblinded, prospective, interventional randomized clinical trial used a stepped-wedge cluster design to compare S100B biomonitoring and control groups at 11 centers in France. Participants included children and adolescents 16 years or younger (hereinafter referred to as children) admitted to the emergency department with minor HT. The enrollment period was November 1, 2016, to October 31, 2021, with a follow-up period of 1 month for each patient. Data were analyzed from March 7 to May 29, 2023, based on the modified intention-to-treat and per protocol populations.

INTERVENTIONS: Children in the control group had CCT scans or were hospitalized according to current recommendations. In the S100B biomonitoring group, blood sampling took place within 3 hours after minor HT, and management depended on serum S100B protein levels. If the S100B level was within the reference range according to age, the children were discharged from the emergency department. Otherwise, children were treated as in the control group.

MAIN OUTCOMES AND MEASURES: Proportion of CCT scans performed (absence or presence of CCT scan for each patient) in the 48 hours following minor HT.

RESULTS: A total of 2078 children were included: 926 in the control group and 1152 in the S100B biomonitoring group (1235 [59.4%] boys; median age, 3.2 [IQR, 1.0-8.5] years). Cranial CT scans were performed in 299 children (32.3%) in the control group and 112 (9.7%) in the S100B biomonitoring group. This difference of 23% (95% CI, 19%-26%) was not statistically significant (P = .44) due to an intraclass correlation coefficient of 0.32. A statistically significant 50% reduction in hospitalizations (95% CI, 47%-53%) was observed in the S100B biomonitoring group (479 [41.6%] vs 849 [91.7%]; P < .001).

CONCLUSIONS AND RELEVANCE: In this randomized clinical trial of effectiveness of the serum S100B level in the management of pediatric minor HT, S100B biomonitoring yielded a reduction in the number of CCT scans and in-hospital observation when measured in accordance with the conditions defined by a clinical decision algorithm.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02819778.

PMID:38502126 | DOI:10.1001/jamanetworkopen.2024.2366

J Sport Rehabil. 2024 Mar 18:1-8. doi: 10.1123/jsr.2023-0166. Online ahead of print.

ABSTRACT

CONTEXT: The purpose of the study was to develop normative ranges and standards for knee and shoulder isokinetic and anthropometric values. These standards can be qualitatively interpreted and allow practitioners to classify isokinetic and anthropometric values more objectively for university-level netball players.

DESIGN: Posttest only observational study design. All players were only evaluated once during the in-season to generate normative ranges.

METHODS: A total of 51 female players volunteered. Participants were evaluated on an isokinetic dynamometer at 60° per second to obtain knee-extensor and knee-flexor values as well as shoulder-flexor and shoulder-extensor values. A total of 16 anthropometric variables were collected including stature, body mass, 8 skinfolds, and 6 circumferences. Between-group differences were calculated to determine whether playing level was a differentiating factor in data.

RESULTS: Normative standards were developed for isokinetic parameters associated with the knee and shoulder joints as well as skinfolds and circumference measures. No statistically significant between-group differences were evident (χ2Kruskal-Wallis[2] = 3.96, P = .140).

CONCLUSION: These standards can be used by coaches and practitioners to set attainable goals for individual players or those from secondary leagues, classify individual and team-based performances, and facilitate decision-making processes.

PMID:38502110 | DOI:10.1123/jsr.2023-0166

JAMA. 2024 Mar 19;331(11):938-950. doi: 10.1001/jama.2024.1059.

ABSTRACT

IMPORTANCE: In January 2023, the US Centers for Disease Control and Prevention and the US Food and Drug Administration noted a safety concern for ischemic stroke among adults aged 65 years or older who received the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine.

OBJECTIVE: To evaluate stroke risk after administration of (1) either brand of the COVID-19 bivalent vaccine, (2) either brand of the COVID-19 bivalent plus a high-dose or adjuvanted influenza vaccine on the same day (concomitant administration), and (3) a high-dose or adjuvanted influenza vaccine.

DESIGN, SETTING, AND PARTICIPANTS: Self-controlled case series including 11 001 Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine (among 5 397 278 vaccinated individuals). The study period was August 31, 2022, through February 4, 2023.

EXPOSURES: Receipt of (1) either brand of the COVID-19 bivalent vaccine (primary) or (2) a high-dose or adjuvanted influenza vaccine (secondary).

MAIN OUTCOMES AND MEASURES: Stroke risk (nonhemorrhagic stroke, transient ischemic attack, combined outcome of nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke) during the 1- to 21-day or 22- to 42-day risk window after vaccination vs the 43- to 90-day control window.

RESULTS: There were 5 397 278 Medicare beneficiaries who received either brand of the COVID-19 bivalent vaccine (median age, 74 years [IQR, 70-80 years]; 56% were women). Among the 11 001 beneficiaries who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there were no statistically significant associations between either brand of the COVID-19 bivalent vaccine and the outcomes of nonhemorrhagic stroke, transient ischemic attack, nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke during the 1- to 21-day or 22- to 42-day risk window vs the 43- to 90-day control window (incidence rate ratio [IRR] range, 0.72-1.12). Among the 4596 beneficiaries who experienced stroke after concomitant administration of either brand of the COVID-19 bivalent vaccine plus a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window for the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine (IRR, 1.20 [95% CI, 1.01-1.42]; risk difference/100 000 doses, 3.13 [95% CI, 0.05-6.22]) and a statistically significant association between vaccination and transient ischemic attack during the 1- to 21-day risk window for the Moderna mRNA-1273.222 COVID-19 bivalent vaccine (IRR, 1.35 [95% CI, 1.06-1.74]; risk difference/100 000 doses, 3.33 [95% CI, 0.46-6.20]). Among the 21 345 beneficiaries who experienced stroke after administration of a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window (IRR, 1.09 [95% CI, 1.02-1.17]; risk difference/100 000 doses, 1.65 [95% CI, 0.43-2.87]).

CONCLUSIONS AND RELEVANCE: Among Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there was no evidence of a significantly elevated risk for stroke during the days immediately after vaccination.

PMID:38502075 | DOI:10.1001/jama.2024.1059

JAMA. 2024 Mar 19;331(11):959-971. doi: 10.1001/jama.2024.0276.

ABSTRACT

IMPORTANCE: Child maltreatment is associated with serious negative physical, psychological, and behavioral consequences.

OBJECTIVE: To review the evidence on primary care-feasible or referable interventions to prevent child maltreatment to inform the US Preventive Services Task Force.

DATA SOURCES: PubMed, Cochrane Library, and trial registries through February 2, 2023; references, experts, and surveillance through December 6, 2023.

STUDY SELECTION: English-language, randomized clinical trials of youth through age 18 years (or their caregivers) with no known exposure or signs or symptoms of current or past maltreatment.

DATA EXTRACTION AND SYNTHESIS: Two reviewers assessed titles/abstracts, full-text articles, and study quality, and extracted data; when at least 3 similar studies were available, meta-analyses were conducted.

MAIN OUTCOMES AND MEASURES: Directly measured reports of child abuse or neglect (reports to Child Protective Services or removal of the child from the home); proxy measures of abuse or neglect (injury, visits to the emergency department, hospitalization); behavioral, developmental, emotional, mental, or physical health and well-being; mortality; harms.

RESULTS: Twenty-five trials (N = 14 355 participants) were included; 23 included home visits. Evidence from 11 studies (5311 participants) indicated no differences in likelihood of reports to Child Protective Services within 1 year of intervention completion (pooled odds ratio, 1.03 [95% CI, 0.84-1.27]). Five studies (3336 participants) found no differences in removal of the child from the home within 1 to 3 years of follow-up (pooled risk ratio, 1.06 [95% CI, 0.37-2.99]). The evidence suggested no benefit for emergency department visits in the short term (<2 years) and hospitalizations. The evidence was inconclusive for all other outcomes because of the limited number of trials on each outcome and imprecise results. Among 2 trials reporting harms, neither reported statistically significant differences. Contextual evidence indicated (1) widely varying practices when screening, identifying, and reporting child maltreatment to Child Protective Services, including variations by race or ethnicity; (2) widely varying accuracy of screening instruments; and (3) evidence that child maltreatment interventions may be associated with improvements in some social determinants of health.

CONCLUSION AND RELEVANCE: The evidence base on interventions feasible in or referable from primary care settings to prevent child maltreatment suggested no benefit or insufficient evidence for direct or proxy measures of child maltreatment. Little information was available about possible harms. Contextual evidence pointed to the potential for bias or inaccuracy in screening, identification, and reporting of child maltreatment but also highlighted the importance of addressing social determinants when intervening to prevent child maltreatment.

PMID:38502070 | DOI:10.1001/jama.2024.0276

Neuro Oncol. 2024 Mar 19:noae053. doi: 10.1093/neuonc/noae053. Online ahead of print.

ABSTRACT

BACKGROUND: Standard treatment for patients with newly diagnosed glioblastoma includes surgery, radiotherapy (RT) and temozolomide (TMZ) chemotherapy (TMZ/RT→TMZ). The proteasome has long been considered a promising therapeutic target because of its role as a central biological hub in tumor cells. Marizomib is a novel pan-proteasome inhibitor that crosses the blood brain barrier.

METHODS: EORTC 1709/CCTG CE.8 was a multicenter, randomized, controlled, open label phase 3 superiority trial. Key eligibility criteria included newly diagnosed glioblastoma, age > 18 years and Karnofsky performance status > 70. Patients were randomized in a 1:1 ratio. The primary objective was to compare overall survival (OS) in patients receiving marizomib in addition to TMZ/RT→TMZ with patients receiving only standard treatment in the whole population, and in the subgroup of patients with MGMT promoter-unmethylated tumors.

RESULTS: The trial was opened at 82 institutions in Europe, Canada and the US. A total of 749 patients (99.9% of planned 750) were randomized. OS was not different between the standard and the marizomib arm (median 17 vs 16.5 months; HR=1.04; p=0.64). PFS was not statistically different either (median 6.0 vs. 6.3 months; HR=0.97; p=0.67). In patients with MGMT promoter-unmethylated tumors, OS was also not different between standard therapy and marizomib (median 14.5 vs 15.1 months, HR=1.13; p=0.27). More CTCAE grade 3/4 treatment-emergent adverse events were observed in the marizomib arm than in the standard arm.

CONCLUSIONS: Adding marizomib to standard temozolomide-based radiochemotherapy resulted in more toxicity, but did not improve OS or PFS in patients with newly diagnosed glioblastoma.

PMID:38502052 | DOI:10.1093/neuonc/noae053