Pub Date : 2021-07-28DOI: 10.23937/2469-5831/1510039
A. Emmanuel, Samson Bimba John, Eseigbe Edwin Ehi, A. Jighjigh, M. Yusuf, C. Akude, Haroun Isah Omeiza, Ojarikre Oniore Jonathan
COVID-19 virus has spread everywhere in Africa and to the 36 states of Nigeria, including the Federal Capital Territory (FCT), Abuja. The outbreak of COVID-19 in Lagos, since February 27, 2020 has generated 158,506 confirmed cases, including 1,969 deaths, as of 8 March 2021. In most cases, community transmission is the prime factor in which the viruses are fast spreading. Fortunately, there has never been a reported incidence of COVID-19 infection on any of the Nigerian university campuses. We assess the risk of sustained transmission at the Bingham University of Nigeria whenever the Coronavirus arrives on our university campus. Risk assessment is achieved through data describing the interaction amongst human-to-human and used facilities on the campus. The data analysis involves a fitted combination of 11 statistical models including inter alia logistic model presented by equation (12). Parameter estimation shows the probability of incidence rates and percentage for coefficient of determination at each level of individual interactions. The cubic regression model of Zankli visitors, Zankli Staff and the inverse regression model of Security Staff yield the highest coefficient of determination with the percentages of 82%, 79% and 74% respectively. This emphasizes the probability that an imported case through the Zankli visitors, Zankli Staff and Security Staff may cause COVID-19 outbreak on the University campus if the Coronavirus protocols are not properly maintained. Under the assumptions that the imported case is a threshold of an index number in the University community, and that the Coronavirus spread through human-to-human and facilities interaction. However, we found that strict compliance to Coronavirus prevention guidelines, which includes regular washing of hands with soap and water, cleaning of hands with alcohol-based hand rub, maintaining of at least 1 metre distance when coughing or sneezing, practicing of physical distancing by avoiding unnecessary travel, staying away from large groups of people, refrain from smoking and other activities that weaken the lungs, staying home whenever you feel unwell and avoid frequent touching of your face are tips for non-pharmaceutical preventive measures.
{"title":"Modeling the Risk Assessment of COVID-19 Pandemic in Bingham University of Nigeria","authors":"A. Emmanuel, Samson Bimba John, Eseigbe Edwin Ehi, A. Jighjigh, M. Yusuf, C. Akude, Haroun Isah Omeiza, Ojarikre Oniore Jonathan","doi":"10.23937/2469-5831/1510039","DOIUrl":"https://doi.org/10.23937/2469-5831/1510039","url":null,"abstract":"COVID-19 virus has spread everywhere in Africa and to the 36 states of Nigeria, including the Federal Capital Territory (FCT), Abuja. The outbreak of COVID-19 in Lagos, since February 27, 2020 has generated 158,506 confirmed cases, including 1,969 deaths, as of 8 March 2021. In most cases, community transmission is the prime factor in which the viruses are fast spreading. Fortunately, there has never been a reported incidence of COVID-19 infection on any of the Nigerian university campuses. We assess the risk of sustained transmission at the Bingham University of Nigeria whenever the Coronavirus arrives on our university campus. Risk assessment is achieved through data describing the interaction amongst human-to-human and used facilities on the campus. The data analysis involves a fitted combination of 11 statistical models including inter alia logistic model presented by equation (12). Parameter estimation shows the probability of incidence rates and percentage for coefficient of determination at each level of individual interactions. The cubic regression model of Zankli visitors, Zankli Staff and the inverse regression model of Security Staff yield the highest coefficient of determination with the percentages of 82%, 79% and 74% respectively. This emphasizes the probability that an imported case through the Zankli visitors, Zankli Staff and Security Staff may cause COVID-19 outbreak on the University campus if the Coronavirus protocols are not properly maintained. Under the assumptions that the imported case is a threshold of an index number in the University community, and that the Coronavirus spread through human-to-human and facilities interaction. However, we found that strict compliance to Coronavirus prevention guidelines, which includes regular washing of hands with soap and water, cleaning of hands with alcohol-based hand rub, maintaining of at least 1 metre distance when coughing or sneezing, practicing of physical distancing by avoiding unnecessary travel, staying away from large groups of people, refrain from smoking and other activities that weaken the lungs, staying home whenever you feel unwell and avoid frequent touching of your face are tips for non-pharmaceutical preventive measures.","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83201590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-28DOI: 10.23937/2469-5831/1510036
Parmaksiz Merve, Boyacioğlu Hayal, G. Pelin, Ezgi Özer Nezaket
In this study, the objective was to compare different estimation methods in diagnostic meta-analysis. In this scope, DerSimonian and Laird (DL), Restricted Maximum Likelihood (REML), Sidik and Jonkman (SJ), Hedges and Olkin (HO), Maximum Likelihood (ML), Paule and Mandel (PM) estimation methods were examined. In the implementation part, effectiveness of Clinical Oral Examination (COE) in predicting the diagnosis of histological dysplasia or Oral Squamous Cell Carcinoma (OSCC) was studied. Meta analysis was performed for the data set obtained from 24 studies in accordance with the criteria. Odds Ratio (OR) was used as the effect size. In meta analysis of the random effect model, according to the DerSimonian and Laird (DL) method, the pooled sensitivity value of COE was calculated as 0.953 (95% CI: 0.895-0.979), pooled selectivity was 0.25 (95% CI: 0.124-0.44), and pooled odds ratio was OR = 6.031 (95% CI: 2.208-16.471). According to these results, it can be concluded that COE was not effective in diagnosis. Among the other estimation methods, DerSimonian and Laird (DL) presented the lowest value for I2 and τ2 (I2 = 66.63%, τ2 = 3.489).
在这项研究中，目的是比较诊断荟萃分析中不同的估计方法。在此范围内，研究了DerSimonian and Laird (DL)、限制最大似然(REML)、Sidik and Jonkman (SJ)、Hedges and Olkin (HO)、最大似然(ML)、Paule and Mandel (PM)估计方法。在实施部分，研究了临床口腔检查(COE)在预测组织学异常增生或口腔鳞状细胞癌(OSCC)诊断中的有效性。对符合标准的24项研究的数据集进行Meta分析。采用优势比(Odds Ratio, OR)作为效应量。在随机效应模型的meta分析中，根据DerSimonian and Laird (DL)方法计算出COE的合并敏感性值为0.953 (95% CI: 0.895 ~ 0.979)，合并选择性值为0.25 (95% CI: 0.124 ~ 0.44)，合并优势比OR = 6.031 (95% CI: 2.208 ~ 16.471)。根据这些结果，可以得出COE在诊断中无效的结论。在其他估计方法中，DerSimonian和Laird (DL)的I2和τ2值最低(I2 = 66.63%， τ2 = 3.489)。
{"title":"Comparison of Estimation Method in Diagnostic Meta-Analysis: An Application in Dentistry","authors":"Parmaksiz Merve, Boyacioğlu Hayal, G. Pelin, Ezgi Özer Nezaket","doi":"10.23937/2469-5831/1510036","DOIUrl":"https://doi.org/10.23937/2469-5831/1510036","url":null,"abstract":"In this study, the objective was to compare different estimation methods in diagnostic meta-analysis. In this scope, DerSimonian and Laird (DL), Restricted Maximum Likelihood (REML), Sidik and Jonkman (SJ), Hedges and Olkin (HO), Maximum Likelihood (ML), Paule and Mandel (PM) estimation methods were examined. In the implementation part, effectiveness of Clinical Oral Examination (COE) in predicting the diagnosis of histological dysplasia or Oral Squamous Cell Carcinoma (OSCC) was studied. Meta analysis was performed for the data set obtained from 24 studies in accordance with the criteria. Odds Ratio (OR) was used as the effect size. In meta analysis of the random effect model, according to the DerSimonian and Laird (DL) method, the pooled sensitivity value of COE was calculated as 0.953 (95% CI: 0.895-0.979), pooled selectivity was 0.25 (95% CI: 0.124-0.44), and pooled odds ratio was OR = 6.031 (95% CI: 2.208-16.471). According to these results, it can be concluded that COE was not effective in diagnosis. Among the other estimation methods, DerSimonian and Laird (DL) presented the lowest value for I2 and τ2 (I2 = 66.63%, τ2 = 3.489).","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"82 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84416785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.23937/2469-5831/1510040
A. Lazzarin, S. Rusconi, A. Antinori, C. Galeone, A. Uglietti, R. Termini, D. Mancusi
Rilpivirine (RPV) is a second-generation non-nucleoside reverse-transcriptase inhibitor used in combination antiretroviral therapy (cART) in naive and experienced HIV-positive adult subjects. To evaluate its efficacy and safety in these patient settings, we performed a metaanalysis of randomized controlled trials with available data at 48 and 96 weeks of follow-up. We considered 4 studies involving 2336 cART-naïve patients and 8 studies involving 3165 cART-experienced virologically controlled patients. Regarding efficacy, the virological response rate and the mean difference in the change from the baseline CD4 cell count were not significantly different between the RPV and comparator arms in both patient groups at both time points. Regarding safety, the discontinuation rates due to any adverse events (AEs), serious AEs, RPV-related AEs and AEs leading to drug discontinuation did not significantly differ from the rates in the comparator group at both time points. A systematic review of lipid changes was also performed: the safety and advantageous metabolic impact of RPV on lipids, especially among cART-naïve subjects at up to 96 weeks of follow-up, were confirmed. Our meta-analysis indicated that RPV-based regimens were effective and tolerable for both types of patients, which was consistent with published data from real-life settings. MetA-AnAlysis *Corresponding author: Dr. Daniela Mancusi, MSc, Biotechnologist, Medical Affairs Department, Infectious Diseases, Janssen-Cilag SpA, Via Michelangelo Buonarroti, 23, 20093 Cologno Monzese, Milano, Italy, Tel: +39-345-9581-944 Check for updates Introduction Rilpivirine (RPV; TMC278; Edurant®) is a secondgeneration non-nucleoside reverse-transcriptase inhibitor (NNRTI) with activity against many viral strains resistant to previous NNRTIs and a moderatehigh genetic barrier to resistance development [1,2]. RPV efficacy and safety have been assessed in registrative randomized controlled clinical trials (RCTs) in HIV-positive treatment-naïve [3-7] and treatmentexperienced patients [8-14] with documented longterm efficacy and tolerability. Real-life data from observational studies [15-21] eventually confirmed these results. Therefore, current Italian [22], European [23], British [24,25] and DHHS (Department of Health and Human Services) [26] HIV/AIDS guidelines recommend the use of RPV as a first-line third agent coupled with a nucleoside reverse transcriptase inhibitor backbone in people living with HIV (PLWH) with CD4 count > 200 cells/μL and HIV RNA < 100,000 copies/mL starting combination antiretroviral therapy (cART) and in optimization strategies represented by RPV-based single tablet regimens (both standard threeISSN: 2469-5831 DOI: 10.23937/2469-5831/1510040 Lazzarin et al. Int J Clin Biostat Biom 2021, 7:040 • Page 2 of 24 • mediated hepatic oxidation, no inhibition or induction of cytochrome P-450 isoenzymes has been reported, and its spectrum of interaction is favorably narrowed [1,2,27]. To date,
{"title":"Efficacy and Safety of Rilpivirine-Based Antiretroviral Therapy in Treatment-Naïve and Treatment-Experienced HIV-1-Positive Patients: A Systematic Review and Meta-Analysis of Randomized Clinical Trials","authors":"A. Lazzarin, S. Rusconi, A. Antinori, C. Galeone, A. Uglietti, R. Termini, D. Mancusi","doi":"10.23937/2469-5831/1510040","DOIUrl":"https://doi.org/10.23937/2469-5831/1510040","url":null,"abstract":"Rilpivirine (RPV) is a second-generation non-nucleoside reverse-transcriptase inhibitor used in combination antiretroviral therapy (cART) in naive and experienced HIV-positive adult subjects. To evaluate its efficacy and safety in these patient settings, we performed a metaanalysis of randomized controlled trials with available data at 48 and 96 weeks of follow-up. We considered 4 studies involving 2336 cART-naïve patients and 8 studies involving 3165 cART-experienced virologically controlled patients. Regarding efficacy, the virological response rate and the mean difference in the change from the baseline CD4 cell count were not significantly different between the RPV and comparator arms in both patient groups at both time points. Regarding safety, the discontinuation rates due to any adverse events (AEs), serious AEs, RPV-related AEs and AEs leading to drug discontinuation did not significantly differ from the rates in the comparator group at both time points. A systematic review of lipid changes was also performed: the safety and advantageous metabolic impact of RPV on lipids, especially among cART-naïve subjects at up to 96 weeks of follow-up, were confirmed. Our meta-analysis indicated that RPV-based regimens were effective and tolerable for both types of patients, which was consistent with published data from real-life settings. MetA-AnAlysis *Corresponding author: Dr. Daniela Mancusi, MSc, Biotechnologist, Medical Affairs Department, Infectious Diseases, Janssen-Cilag SpA, Via Michelangelo Buonarroti, 23, 20093 Cologno Monzese, Milano, Italy, Tel: +39-345-9581-944 Check for updates Introduction Rilpivirine (RPV; TMC278; Edurant®) is a secondgeneration non-nucleoside reverse-transcriptase inhibitor (NNRTI) with activity against many viral strains resistant to previous NNRTIs and a moderatehigh genetic barrier to resistance development [1,2]. RPV efficacy and safety have been assessed in registrative randomized controlled clinical trials (RCTs) in HIV-positive treatment-naïve [3-7] and treatmentexperienced patients [8-14] with documented longterm efficacy and tolerability. Real-life data from observational studies [15-21] eventually confirmed these results. Therefore, current Italian [22], European [23], British [24,25] and DHHS (Department of Health and Human Services) [26] HIV/AIDS guidelines recommend the use of RPV as a first-line third agent coupled with a nucleoside reverse transcriptase inhibitor backbone in people living with HIV (PLWH) with CD4 count > 200 cells/μL and HIV RNA < 100,000 copies/mL starting combination antiretroviral therapy (cART) and in optimization strategies represented by RPV-based single tablet regimens (both standard threeISSN: 2469-5831 DOI: 10.23937/2469-5831/1510040 Lazzarin et al. Int J Clin Biostat Biom 2021, 7:040 • Page 2 of 24 • mediated hepatic oxidation, no inhibition or induction of cytochrome P-450 isoenzymes has been reported, and its spectrum of interaction is favorably narrowed [1,2,27]. To date,","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83867850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01Epub Date: 2021-06-28DOI: 10.23937/2469-5831/1510038
Greg Dyson
Background: Phase III superiority clinical trials have negative results (new treatment is not statistically better than standard of care) due to a number of factors, including patient and disease heterogeneity. However, even a treatment regime that fails to show population-level clinical improvement will have a subgroup of patients that attain a measurable clinical benefit.
Objective: The goal of this paper is to modify the Patient Rule-Induction Method to identify statistically significant subgroups, defined by clinical and/or demographic factors, of the clinical trial population where the experimental treatment performs better than the standard of care and better than observed in the entire clinical trial sample.
Results: We illustrate this method using part A of the SUCCESS clinical trial, which showed no overall difference between treatment arms: HR (95% CI) = 0.97 (0.78, 1.20). Using PRIM, we identified one subgroup defined by the mutational profile in BRCA1 which resulted in a significant benefit for adding Gemcitabine to the standard treatment: HR (95% CI) = 0.59 (0.40, 0.87).
Conclusion: This result demonstrates that useful information can be extracted from existing databases that could provide insight into why a phase III trial failed and assist in the design of future clinical trials involving the experimental treatment.
{"title":"An Application of the Patient Rule-Induction Method to Detect Clinically Meaningful Subgroups from Failed Phase III Clinical Trials.","authors":"Greg Dyson","doi":"10.23937/2469-5831/1510038","DOIUrl":"https://doi.org/10.23937/2469-5831/1510038","url":null,"abstract":"<p><strong>Background: </strong>Phase III superiority clinical trials have negative results (new treatment is not statistically better than standard of care) due to a number of factors, including patient and disease heterogeneity. However, even a treatment regime that fails to show population-level clinical improvement will have a subgroup of patients that attain a measurable clinical benefit.</p><p><strong>Objective: </strong>The goal of this paper is to modify the Patient Rule-Induction Method to identify statistically significant subgroups, defined by clinical and/or demographic factors, of the clinical trial population where the experimental treatment performs better than the standard of care and better than observed in the entire clinical trial sample.</p><p><strong>Results: </strong>We illustrate this method using part A of the SUCCESS clinical trial, which showed no overall difference between treatment arms: HR (95% CI) = 0.97 (0.78, 1.20). Using PRIM, we identified one subgroup defined by the mutational profile in BRCA1 which resulted in a significant benefit for adding Gemcitabine to the standard treatment: HR (95% CI) = 0.59 (0.40, 0.87).</p><p><strong>Conclusion: </strong>This result demonstrates that useful information can be extracted from existing databases that could provide insight into why a phase III trial failed and assist in the design of future clinical trials involving the experimental treatment.</p>","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39506854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-03DOI: 10.23937/2469-5831/1510022
Yifan Wang, Tian You, Martin Lysy
{"title":"A Heteroscedastic Accelerated Failure Time Model for Survival Analysis","authors":"Yifan Wang, Tian You, Martin Lysy","doi":"10.23937/2469-5831/1510022","DOIUrl":"https://doi.org/10.23937/2469-5831/1510022","url":null,"abstract":"","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"210 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73280283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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