Please select a file to upload
The file should contain at least six columns. Labelling of columns is case sensitive.
The first column should be labelled author and contain the name of the study author. The author name must be unique for each study.
The second column should be labelled year and contain the year of publication.
The third column should be labelled TP and contain the number of patients with a true positive test result.
The fourth column should be labelled FN and contain the number of patients with a false negative test result.
The fifth column should be labelled FP and contain the number of patients with a false positive test result.
The sixth column should be labelled TN and contain the number of patients with a true negative test result.
Including quality assessment data (optional)
To allow the quality assessment results from the QUADAS-2 tool to be incorporated into the plots an additional seven columns are required.
The seventh column should be labelled rob_PS , representing the risk of bias in terms of the patient selection.
The eighth column should be labelled rob_IT , representing the risk of bias in terms of the index test.
The ninth column should be labelled rob_RS , representing the risk of bias in terms of the reference standard.
The tenth column should be labelled rob_FT , representing the risk of bias in terms of the flow and timing.
The eleventh column should be labelled ac_PS , representing the applicability concerns in terms of the patient selection.
The twelfth column should be labelled ac_IT , representing the applicability concerns in terms of the index test.
The thirteenth column should be labelled ac_RS , representing the applicability concerns in terms of the reference standard.
These columns should contain the numbers 1, 2 or 3 which represent low, high or unclear risk of bias/applicability concerncs respectively.
For information about the QUADAS-2 tool and how to use it please visit:
https://www.bristol.ac.uk/population-health-sciences/projects/quadas/quadas-2/Including covariates (optional)
If any covariates are to be added to the file they should be included as the last columns in the file. If quality assessment data is not included in the file the covariates should be entered starting at the seventh column. If quality assessment data is included in the file the covariate data should be entered starting at the fourteenth column. Multiple covariates can be entered.
The default dataset, pre-loaded on the 'Data for Analysis' tab will be used for analysis if no file is selected. The 'Data for Analysis' tab will automatically update once a file is successfully loaded.
The default datasets can be downloaded using the buttons in the sidebar and used as templates to enter your own data.
Sensitivity analysis
To ensure the correct studies are excluded from sensitivity analyses please ensure that study data rows are ordered by the 'author' column alphabetically from A to Z prior to uploading to MetaDTA (Excel can do this easily).
The default dataset uses data from a systematic review investigating the accuracy of an informant-based questionnaire, for detection of all cause dementia in adults. The dataset consists of thirteen studies assessing the use of the IQCODE (Informant Questionnaire on Cognitive Decline in the Elderly) tool for identifying adults with dementia within a secondary care setting.
The IQCODE tool contains a number of questions which are scored on a five point scale. The IQCODE tool has a number of different variants, depending on how many questions are asked. The questions are based on the performance of everyday tasks related to cognitive function. These are then rated on a scale of 1-5. The final score is an average score for each question. The IQCODE tool is only a screening tool and does not offer a definitive diagnosis of dementia.
Under the 'Select example dataset' option there are four different datasets to choose from. The default is the 'Standard' dataset, which includes the author and year of each study along with the true positives (TP), false positives (FP), false negatives (FN) and true negatives (TN). The other options add data onto this 'Standard' dataset and highlight how datasets with quality assessment scores and/or covariates should be displayed.
With this dataset there are three different covariates. The first being the country in which each individual study was conducted. The second is the threshold used in each individual study. In this case if an individuals final score was higher than the threshold the individual was classified as having dementia and would require further diagnosis. The final covariate is labelled as 'IQCODE' and indicates which variant of the tool was used in each individual study. The variants are identified by the number of questions used in the questionnaire. There are three different variants the 16-item, 26-item and 32-item.
