1. Human Biology and Medicine
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Research: Adequate statistical power in clinical trials is associated with the combination of a male first author and a female last author

  1. Willem M Otte
  2. Joeri K Tijdink
  3. Paul L Weerheim
  4. Herm J Lamberink
  5. Christiaan H Vinkers  Is a corresponding author
  1. University Medical Center Utrecht/Utrecht University, Netherlands
  2. VU University, Netherlands
  3. University Medical Center Utrecht/Utrecht University, The Netherlands
Feature Article
Cite this article as: eLife 2018;7:e34412 doi: 10.7554/eLife.34412
8 figures, 2 tables and 1 data set

Figures

Percentage of adequately powered trials for the four different gender combinations of first and last author.

(A) Percentage of trials with power > 0.8 published between 1974 and 2017 for the four gender combinations (left panel) and for four periods (1975–1985; 1985–1995; 1995–2005; >2005) during this time (right panel). (B) Percentage of trials published with power > 0.7 (left) and power > 0.9 (right) for the four gender combinations. (C) Percentage of trials with power > 0.8 for the four gender combinations, including the trials were gender could not be determined for the first and/or last author (‘unknown’). Error bars represent the 95% confidence interval for proportions for all panels.

https://doi.org/10.7554/eLife.34412.002
Percentage of adequately powered trials when the gender of the first and last author is male, female or unknown.

Left: Percentage of trials with power > 0.8 plotted for the gender of the first author (top) and the last author (bottom). Right: Percentage of trials with power > 0.8 plotted for four periods (1975–1985; 1985–1995; 1995–2005; >2005) for the gender of the first author (top) and the last author (bottom). Error bars represent the 95% confidence interval for proportions for all panels.

https://doi.org/10.7554/eLife.34412.003
The proportion of included trials mapped per country on a white to red color scale (range: 0 – 24%).

The highest proportion of first authors were affiliated with an institution in the United States. Countries not present in any affiliation are plotted in gray.

https://doi.org/10.7554/eLife.34412.006
The influence of geography on the percentage of trials that are adequately powered.

(A) Percentage of trials with power > 0.8 for the four gender combinations of first and last author within the three country groups. Error bars represent the 95% confidence interval for proportions. (B) A logistic regression multivariable model (see "Data analysis and statistical model" below) can be used to predict the probability that a trial will have a power above a certain value. Here the predicted probabilities that trials will have power > 0.8 are plotted as a function of year for the four gender combinations in the three country groups. The predicted probabilities are averaged across medical disciplines and plotted as mean and 95% confidence intervals.

https://doi.org/10.7554/eLife.34412.007
Percentage of adequately powered trials, for the four gender combinations of the first and the last author, within 21 major medical disciplines.

Error bars represent the 95% confidence interval for proportions.

https://doi.org/10.7554/eLife.34412.008
The percentage of the total number of trials underlying the four gender combinations within 21 major medical disciplines.

Error bars represent the 95% confidence interval for proportions.

https://doi.org/10.7554/eLife.34412.009
The percentage of trials for the different gender combinations and periods studied.

Left: The number and percentage of trials underlying the power calculations for the four gender combinations. Right: The corresponding percentage of the total number of trials underlying the four gender combinations for the four periods studied (1975–1985; 1985–1995; 1995–2005; >2005). Error bars represent the 95% confidence interval for proportions for both panels.

https://doi.org/10.7554/eLife.34412.010
Flow diagram of the 31,873 trials selected for analysis.

Trials were analyzed if published after 1974, included in a significant meta-analysis in a systematic review and gender data was extractable for both the first and the last author.

https://doi.org/10.7554/eLife.34412.011

Tables

Table 1
Model estimates for the variables fitted against adequately powered trials.
https://doi.org/10.7554/eLife.34412.004
VariablesOdds ratio95% CIZ valueP value
Author combination
Both females1.00 (ref.)
Both males1.281.171.415.22<0.0001
Female - male (last)1.251.131.394.29<0.0001
Male - female (last)2.081.872.3013.94<0.0001
Time
Publication year1.031.021.0312.05<0.0001
Country group
Anglosphere1.00 (ref.)
Europe0.760.710.818.87<0.0001
Non-western0.870.800.943.69<0.0001
Medical discipline
Allergy & intolerance1.00 (ref)
Blood disorders0.450.340.625.11<0.0001
Child health0.470.360.615.68<0.0001
Complementary medicine0.230.170.319.14<0.0001
Consumer strategies0.660.411.031.800.072
Dentistry & oral health1.050.681.590.210.832
Developmental problems0.690.471.001.980.048
Ear, nose & throat0.370.240.554.77<0.0001
Effective health systems0.750.531.071.570.115
Endocrine & metabolic0.290.200.426.51<0.0001
Eyes & vision0.560.380.813.020.003
Gastroenterology & hepatology0.490.380.655.07<0.0001
Genetic disorders0.190.120.307.09<0.0001
Gynaecology0.690.520.922.580.01
Health & safety at work0.240.130.424.74<0.0001
Heart & circulation0.290.220.398.24<0.0001
Infectious disease0.610.470.803.62<0.0001
Kidney disease0.800.581.121.280.201
Lungs & airways0.350.270.467.56<0.0001
Mental health0.530.400.714.40<0.0001
Neonatal care0.470.340.644.68<0.0001
Neurology0.560.420.744.08<0.0001
Orthopaedics & trauma0.790.601.051.630.103
Pain & anaesthesia0.640.490.843.230.001
Pregnancy & childbirth0.580.440.773.76<0.0001
Public health1.230.781.920.890.372
Rheumatology0.750.571.002.020.043
Skin disorders0.890.651.230.690.488
Tobacco, drugs & alcohol0.340.260.467.39<0.0001
Urology1.040.741.450.210.834
Wounds0.360.210.613.73<0.0001
Table 2
Model estimates from the sensitivity analysis (with individual countries) for the variables fitted against adequately powered trials.
https://doi.org/10.7554/eLife.34412.005
VariablesOdds ratio95% CIZ valueP value
Author combination
Both females1.00 (ref.)
Both males1.251.131.374.58<0.001
Female - male (last)1.191.071.323.280.001
Male - female (last)1.981.782.1912.95<0.001
Time
Publication year1.021.021.0314.5<0.001
Country
Argentina1.00 (ref.)
Australia0.790.521.191.120.261
Austria1.310.842.021.190.232
Bangladesh3.292.005.414.69<0.001
Belgium0.940.611.450.290.775
Brazil0.980.631.510.100.92
Canada1.160.781.720.720.474
Chile0.740.391.420.890.371
China1.200.81.810.870.383
Colombia1.951.173.262.550.011
Costa Rica0.000.00Inf0.140.891
Croatia0.470.221.031.880.06
Czech Republic0.710.451.131.450.147
Denmark1.240.821.871.030.303
Egypt1.781.132.792.500.013
Finland0.880.581.320.630.527
France0.910.611.370.440.663
Gambia1.050.561.990.160.87
Germany0.900.61.340.530.593
Ghana0.840.481.480.610.544
Greece0.460.290.753.120.002
Hong Kong1.370.892.111.440.15
Hungary2.871.754.74.18<0.001
India0.890.581.350.560.573
Indonesia0.710.341.480.930.354
Iran1.140.731.790.590.557
Ireland0.800.491.320.870.387
Israel0.800.511.260.980.328
Italy1.030.691.530.150.881
Japan0.350.220.534.83<0.001
Jordan3.912.097.324.27<0.001
Kenya0.420.181.001.970.049
Korea1.561.022.392.070.038
Lebanon1.360.752.461.010.311
Malawi0.120.030.522.830.005
Malaysia0.780.341.790.590.552
Mali0.750.291.910.610.543
Mexico1.070.621.850.250.8
Netherlands0.710.471.071.620.106
New Zealand1.280.762.140.940.349
Nigeria1.320.702.480.870.386
Norway0.890.561.410.490.624
Pakistan0.930.481.830.200.844
Papua New Guinea0.000.00Inf0.100.918
Peru0.990.571.70.040.967
Poland0.390.220.683.290.001
Portugal3.171.845.454.17<0.001
Qatar0.000.00Inf0.110.916
Saudi Arabia0.540.300.982.020.043
Singapore1.140.681.930.500.614
Slovenia0.000.00Inf0.110.91
South Africa1.240.791.960.930.355
Spain1.080.711.620.350.73
Sweden1.240.831.851.030.301
Switzerland0.660.431.021.890.059
Taiwan0.450.290.713.430.001
Thailand1.530.992.371.930.053
Turkey0.640.420.982.060.039
Uganda1.270.562.880.580.56
UK1.250.841.851.100.273
USA1.420.962.101.780.076
Venezuela5.253.228.546.67<0.001
Vietnam0.000.00Inf0.120.907
Zimbabwe1.930.904.121.700.089
Other countries0.750.481.171.280.201
Medical discipline
Allergy & intolerance1.00 (ref.)
Blood disorders0.490.390.635.79<0.001
Child health0.550.450.675.87<0.001
Complementary medicine0.260.200.3311.21<0.001
Consumer strategies0.940.661.340.350.73
Dentistry & oral health1.431.071.922.410.016
Developmental problems0.780.581.051.640.101
Ear, nose & throat0.510.390.684.66<0.001
Effective health systems0.850.631.141.110.269
Endocrine & metabolic0.40.300.536.58<0.001
Eyes & vision0.510.380.704.27<0.001
Gastroenterology & hepatology0.560.460.695.41<0.001
Genetic disorders0.290.200.426.51<0.001
Gynaecology0.820.661.011.840.066
Health & safety at work0.540.370.793.160.002
Heart & circulation0.340.270.439.43<0.001
Infectious disease0.80.650.992.090.036
Kidney disease0.710.550.922.590.01
Lungs & airways0.470.380.587.04<0.001
Mental health0.60.480.754.58<0.001
Neonatal care0.380.290.487.81<0.001
Neurology0.70.570.873.260.001
Orthopaedics & trauma1.180.961.461.560.12
Pain & anaesthesia0.730.600.902.920.003
Pregnancy & childbirth0.690.550.853.400.001
Public health1.721.242.373.270.001
Rheumatology0.970.781.200.310.757
Skin disorders1.260.991.591.890.058
Tobacco. drugs & alcohol0.40.320.507.97<0.001
Urology1.271.001.631.920.054
Wounds0.80.591.081.440.15

Data availability

Data and scripts are available via the Open Science Framework (https://osf.io/ud2jw/) Parsing of genders can be done via genderize.io.

The following previously published data sets were used
  1. 1
    Temporal RCT power
    1. Willem M. Otte
    (2017)
    Available at Open Science Framework.

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