Target Sample Size | ScienceGate

ObjectivesTo investigate differences between target and actual sample sizes, and what study characteristics were associated with sample sizes.DesignObservational study.SettingThe large trial registries of clinicaltrials.gov (starting in 1999) and ANZCTR (starting in 2005) through to 2021.ParticipantsOver 280 000 interventional studies excluding studies that were withheld, terminated for safety reasons or were expanded access.Main outcome measuresThe actual and target sample sizes, and the within-study ratio of the actual to target sample size.ResultsMost studies were small: the median actual sample sizes in the two databases were 60 and 52. There was a decrease over time in the target sample size of 9%–10% per 5 years, and a larger decrease of 18%–21% per 5 years for the actual sample size. The actual-to-target sample size ratio was 4.1% lower per 5 years, meaning more studies (on average) failed to hit their target sample size.ConclusionRegistered studies are more often under-recruited than over-recruited and worryingly both target and actual sample sizes appear to have decreased over time, as has the within-study gap between the target and actual sample size. Declining sample sizes and ongoing concerns about underpowered studies mean more research is needed into barriers and facilitators for improving recruitment and accessing data.

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A systematic review of pregnancy exposure registries: examination of protocol-specified pregnancy outcomes, target sample size, and comparator selection

Pharmacoepidemiology and Drug Safety ◽

10.1002/pds.4150 ◽

2016 ◽

Vol 26 (2) ◽

pp. 208-214 ◽

Cited By ~ 16

Author(s):

Kate Gelperin ◽

Hoda Hammad ◽

Kira Leishear ◽

Steven T. Bird ◽

Lockwood Taylor ◽

...

Keyword(s):

Systematic Review ◽

Sample Size ◽

Pregnancy Outcomes ◽

Target Sample Size ◽

Target Sample

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A nonparametric repeated significance test with adaptive target sample size

Journal of Statistical Planning and Inference ◽

10.1016/j.jspi.2006.06.031 ◽

2007 ◽

Vol 137 (3) ◽

pp. 869-878 ◽

Cited By ~ 2

Author(s):

Vladimir Pozdnyakov ◽

Joseph Glaz

Keyword(s):

Sample Size ◽

Significance Test ◽

Target Sample Size ◽

Target Sample

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Using Facebook and LinkedIn to Recruit Nurses for an Online Survey

Western Journal of Nursing Research ◽

10.1177/0193945917740706 ◽

2017 ◽

Vol 41 (1) ◽

pp. 96-110 ◽

Cited By ~ 7

Author(s):

Yehudis Stokes ◽

Amanda Vandyk ◽

Janet Squires ◽

Jean-Daniel Jacob ◽

Wendy Gifford

Keyword(s):

Social Media ◽

Sample Size ◽

Cost Efficiency ◽

Online Survey ◽

Limited Information ◽

Participant Recruitment ◽

Level Of Education ◽

Target Sample Size ◽

Target Sample ◽

English Speaking

Social media is an emerging tool used by researchers; however, limited information is available on its use for participant recruitment specifically. The purpose of this article is to describe the use of Facebook and LinkedIn social media sites in the recruitment of nurses for an online survey, using a 5-week modified online Dillman approach. Within 3 weeks, we exceeded our target sample size ( n = 170) and within 5 weeks recruited 267 English-speaking nurses ( n = 172, Facebook; n = 95, LinkedIn). Advantages included speed of recruitment, cost-efficiency, snowballing effects, and accessibility of the researcher to potential participants. However, an analysis of the recruited participants revealed significant differences when comparing the sociodemographics of participants recruited through Facebook and LinkedIn, specifically relating to the characteristics of sex, age, and level of education. Differences between Facebook and LinkedIn as recruitment platforms should be considered when incorporating these strategies.

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Persepsi Mahasiswa Akuntansi Terhadap Independensi Akuntan Publik: Studi Empirik pada Mahasiswa Akuntansi di Bandung

Jurnal Akuntansi Maranatha ◽

10.28932/jam.v13i2.4020 ◽

2021 ◽

Vol 13 (2) ◽

pp. 378-387

Author(s):

Trimanto Setyo Wardoyo ◽

Tatik Budiningsih ◽

Herman Kambono ◽

Elvira Veronica

Keyword(s):

Sample Size ◽

Accounting Students ◽

Accounting Profession ◽

Proper Place ◽

Target Sample Size ◽

Perceptions Of Students ◽

Target Sample ◽

Public Accountants ◽

The City ◽

Public Accountant

Abstract This study aims to determine the perceptions of accounting students towards the independence of public accountants in the city of Bandung. Positive perceptions indicate that the accounting profession, especially public accountants, has a proper place in accounting students. Through a questionnaire distributed with a sample of accounting students in the city of Bandung, with a target sample size of 60 students. From 137 respondents gathered, it can be seen based on the results of the analysis that students majoring in accounting in Bandung perceive that public accountants in Indonesia are not independent. In addition, the results of this study are expected to be inference for accounting students in Indonesia. The results of this study also show that there are differences in the perceptions of students majoring in accounting in Bandung who have never and who have taken auditing courses on the independence of public accountants in Indonesia. Keywords: Perception, Independence, Accounting Profession, and Public Accountant

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P062 A SYSTEMATIC REVIEW ON POWER ESTIMATION TO SUPPORT SAMPLE SIZE CALCULATION FOR RANDOMISED TRIALS IN INFLAMMATORY BOWEL DISEASE

Inflammatory Bowel Diseases ◽

10.1093/ibd/zaa010.021 ◽

2020 ◽

Vol 26 (Supplement_1) ◽

pp. S9-S9

Author(s):

Svetlana Lakunina ◽

Zipporah Iheozor-Ejiofor ◽

Morris Gordon ◽

Daniel Akintelure ◽

Vassiliki Sinopoulou

Keyword(s):

Inflammatory Bowel Disease ◽

Sample Size ◽

Bowel Disease ◽

Sample Size Calculation ◽

Sample Size Estimation ◽

Power Calculation ◽

Size Estimation ◽

Target Sample ◽

Inflammatory Bowel ◽

Randomised Controlled

Abstract Inflammatory bowel disease is a collection of disorders of the gastrointestinal tract, characterised by relapsing and remitting inflammation. Studies have reported several pharmacological or non-pharmacological interventions being effective in the management of the disease. Sample size estimation with power calculation is necessary for a trial to detect the effect of an intervention. This project critically evaluates the sample size estimation and power calculation reported by randomised controlled studies of inflammatory bowel disease management to effectively conclude appropriateness of the studies results. We conducted a literature search in the Cochrane database to identify systematic literature reviews. Their reference lists were screened, and studies were selected if they met the inclusion criteria. The data was extracted based on power calculation parameters and outcomes, results were analysed and summarised in percentages, means and graphs. We screened almost all trials about the management of inflammatory bowel disease published in the past 25 years. 232 studies were analysed, of which 167 reported power calculation. Less than half (48%) of these studies achieved their target sample size, needed for them to accurately conclude that the interventions were effective. Moreover, the average minimal difference those studies were aimed to detect was 30%, which could be not enough to prove the effect of an intervention. To conclude inaccurate power calculations and failure to achieve the target sample sizes can lead to errors in the results on how effective an intervention is in the management of inflammatory bowel disease.

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A systematic review of the “promising zone” design

Trials ◽

10.1186/s13063-020-04931-w ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Julia M. Edwards ◽

Stephen J. Walters ◽

Cornelia Kunz ◽

Steven A. Julious

Keyword(s):

Systematic Review ◽

Sample Size ◽

Interim Analysis ◽

Practical Implementation ◽

Ethical Concerns ◽

Target Sample Size ◽

Maximum Sample Size ◽

Sample Size Calculations ◽

Original Target ◽

Design Simplicity

Abstract Introduction Sample size calculations require assumptions regarding treatment response and variability. Incorrect assumptions can result in under- or overpowered trials, posing ethical concerns. Sample size re-estimation (SSR) methods investigate the validity of these assumptions and increase the sample size if necessary. The “promising zone” (Mehta and Pocock, Stat Med 30:3267–3284, 2011) concept is appealing to researchers for its design simplicity. However, it is still relatively new in the application and has been a source of controversy. Objectives This research aims to synthesise current approaches and practical implementation of the promising zone design. Methods This systematic review comprehensively identifies the reporting of methodological research and of clinical trials using promising zone. Databases were searched according to a pre-specified search strategy, and pearl growing techniques implemented. Results The combined search methods resulted in 270 unique records identified; 171 were included in the review, of which 30 were trials. The median time to the interim analysis was 60% of the original target sample size (IQR 41–73%). Of the 15 completed trials, 7 increased their sample size. Only 21 studies reported the maximum sample size that would be considered, for which the median increase was 50% (IQR 35–100%). Conclusions Promising zone is being implemented in a range of trials worldwide, albeit in low numbers. Identifying trials using promising zone was difficult due to the lack of reporting of SSR methodology. Even when SSR methodology was reported, some had key interim analysis details missing, and only eight papers provided promising zone ranges.

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The worldwide clinical trial research response to the COVID-19 pandemic - the first 100 days

F1000Research ◽

10.12688/f1000research.26707.2 ◽

2020 ◽

Vol 9 ◽

pp. 1193

Author(s):

Perrine Janiaud ◽

Cathrine Axfors ◽

Janneke van't Hooft ◽

Ramon Saccilotto ◽

Arnav Agarwal ◽

...

Keyword(s):

Clinical Trials ◽

Sample Size ◽

Treatment Options ◽

Descriptive Analysis ◽

Public Attention ◽

Clinical Trial Research ◽

Target Sample Size ◽

Vaccine Trials ◽

Care Workers ◽

The Usa

Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited <20% of the targeted sample; 27 between 20-50%; and 30 over 50% (median 14.8% [IQR 2.0-62.0%]). Conclusions: The size and speed of the COVID-19 clinical trials agenda is unprecedented. However, most trials were small investigating a small fraction of treatment options. The feasibility of this research agenda is questionable, and many trials may end in futility, wasting research resources. Much better coordination is needed to respond to global health threats.

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Does progression-free-survival (PFS) correlate with overall- and cancer-specific survival (OS/CSS) in randomized clinical trials (RCTs) exploring the addition of hormonal therapy (HT) to radiotherapy (RT) for early prostate cancer (EPC)? Analysis of six RCTs

Journal of Clinical Oncology ◽

10.1200/jco.2007.25.18_suppl.5056 ◽

2007 ◽

Vol 25 (18_suppl) ◽

pp. 5056-5056

Author(s):

E. M. Ruggeri ◽

E. Bria ◽

P. Carlini ◽

F. Cuppone ◽

M. Milella ◽

...

Keyword(s):

Sample Size ◽

Randomized Clinical Trials ◽

Progression Free Survival ◽

Outcome Data ◽

Phase Iii ◽

Cancer Specific Survival ◽

End Point ◽

Target Sample Size ◽

Phase Iii Trials ◽

Beta Coefficient

5056 Background: Although PFS is considered the standard primary end-point in EPC, the correlation with OS has never been explored in RCTs randomizing patients (pts) to HT plus radiotherapy (RT) versus RT. Given the relatively long prognosis in this disease setting, the correlation between PFS and CSS should be investigated as well. Methods: All phase III trials reporting all outcome’ data were considered eligible. The correlation has been explored according to a linear regression model considering both each single outcome pair (PFS, OS and CSS rates) for all arms, and each reported Hazard Ratio (HRs). The correlation was estimated according to both the Pearson- (r) and R2-coefficient (parametric) and the Spearman coefficient (Rho, non-parametric). A sensitivity analysis in 2 subgroups (long- and short-term HT) to test for effect robustness has been accomplished as well. A model to determine the target sample size to determine CSS benefit of 3%, 4%, 6% and 7% months, respectively, was calculated as well. Results: Six RCTs (4,212 pts) were collected (follow-up range: 4.5–7.6 years). In the overall population, when considering the crude rates, a linear stronger correlation was found between PFS and CSS (r=0.71, R2=0.51, p=0.003; Rho=0.75, p=0.005), rather than with OS (r=0.55, R2=0.30, p=0.06; Rho=0.78, p=0.11). Again, when considering HRs, a linear stronger correlation was found between PFS and CSS (r=0.87, R2=0.76, p=0.02; Rho=0.94, p=0.005), rather than with OS (r=0.75, R2=0.56, p=0.08; Rho=0.77, p=0.07). Similar correlations were found whatever subgroups was explored. The sample size model (on the basis of the beta-coefficient=0.71), calculate 4,575, 2,006, 1,115 and 700 pts to improve PFS of 4%, 6%, 8%, and 10% months, which means to improve CSS of 2.8%, 4.3%, 5.7% and 7.1%, respectively. Conclusions: The correlation between PFS and CSS in RCTs exploring the benefit of adding HT to RT for EPC is significant, and suggests its further investigation as surrogate end-point. The natural history of the disease clearly explains the stronger correlation of PFS with CSS rather than with OS. No significant financial relationships to disclose.

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The worldwide clinical trial research response to the COVID-19 pandemic - the first 100 days

F1000Research ◽

10.12688/f1000research.26707.1 ◽

2020 ◽

Vol 9 ◽

pp. 1193 ◽

Cited By ~ 2

Author(s):

Perrine Janiaud ◽

Cathrine Axfors ◽

Janneke van't Hooft ◽

Ramon Saccilotto ◽

Arnav Agarwal ◽

...

Keyword(s):

Clinical Trials ◽

Sample Size ◽

Treatment Options ◽

Descriptive Analysis ◽

Public Attention ◽

Clinical Trial Research ◽

Target Sample Size ◽

Vaccine Trials ◽

Care Workers ◽

The Usa

Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited <20% of the targeted sample; 27 between 20-50%; and 30 over 50% (median 14.8% [IQR 2.0-62.0%]). Conclusions: The size and speed of the COVID-19 clinical trials agenda is unprecedented. However, most trials were small investigating a small fraction of treatment options. The feasibility of this research agenda is questionable, and many trials may end in futility, wasting research resources. Much better coordination is needed to respond to global health threats.

Download Full-text