Tools+(all+domains)

General
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 * **Mind the Gap:** A mnemonic for designing and reporting randomized trials.
 * **Risk of Bias Tool:** A form that can be used as a template for completing Risk of Bias assessments.

Download:


 * **Risk of Bias Guidelines**: A table based on guidelines from Chapter 8 of the Cochrane Collaboration'shandbook (Cochrane Handbook) and decision rules used by the Alberta Research Centre for Health Evidence (ARCHE).
 * **SPIRIT Checklist:** Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT Executive Summary; //checklist under development//).
 * **Cochrane Training:** Assessing risk of bias in a systematic review
 * **StaR Child Health:** An initiative that seeks to improve the quality of design, conduct, and reporting of pediatric clinical research by promoting the use of modern research standards. [|www.starchildhealth.org]
 * **Maternal Infant Child & Youth Research Network (MICYRN):** A collaborative national initiative to build capacit for high quality clinical research in Canada. MICYRN links 17 participating academic health centres and hundreds of investigation teams across the country. [|www.micyrn.ca]
 * **EQUATOR Network:** An international initiative that seeks to improve reliability and value of medical research literature by promoting transparent and accurate reporting of research studies. [|www.equator-network.org]
 * **TrustTheEvidence.net:** A series of blogs on evidence-based medicine. []
 * **Centre for Evidence Based Medicine:** CEBM is based in Oxford and aims to develop, teach, and promote evidence-based health care. []

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Sequence generation

 * Appropriate means of generating a random sequence:**
 * Referring to a random number table
 * Using a computer random number generator
 * Coin tossing
 * Shuffling cards or envelopes
 * Throwing dice
 * Drawing of lots
 * Minimization


 * Random number table:** The WHO gives an example of a random number table and instructions for its use.


 * Creating random numbers:** A number of stats programs will allow you to generate random numbers. When using this technique, it is necessary to have an //a priori// classification system that will be used to assign individuals to the different treatment groups. For example, using a program like Excel will allow you to generate random numbers between 0 and 1, and you may decide that any individuals with numbers <0.5 will be assigned to Group A and any individuals with numbers >=0.5 will be assigned to Group B.

The syntax for various programs is provided below:
 * Microsoft Excel: =rand
 * Stata: gen x = runiform
 * R: random.seed
 * runif(n, min=0, max=1)


 * Randomization services:** There are also online services that can create your randomization sequence. Some examples are provided below.
 * Randomize.net: []
 * Sealed Envelope: []
 * Directory of Randomisation Software and Services: []

Clinical trials coordinating centres may also offer randomization services.
 * EPICORE Centre (University of Alberta)

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Allocation concealment

 * Appropriate means of concealing group allocation:**
 * Central allocation (including telephone, web-based, and pharmacy-controlled randomization)
 * Sequentially numbered drug containers of identical appearance
 * Sequentially numbered, opaque, sealed envelopes

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 * Appropriate means of blinding study participants, personnel, and outcome assessors:**
 * No blinding or incomplete blinding, but the outcome is not likely to be influenced by lack of blinding
 * Blinding of key personnel ensured, and unlikely that blinding could have been broken

Practical tips for blinding surgical trials: Karanicolas et al. 2010 Recommendations for blinding behavioural interventions: Friedberg et al. 2010 PubMed]

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Incomplete outcome data

 * Appropriate handling of outcome data:**
 * No missing outcome data
 * Reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias)
 * Missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups
 * For dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate
 * For continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size
 * Missing data have been imputed using appropriate methods

CONSORT flow diagram: The CONSORT flow diagram outlines the flow of study participants through the stages of an RCT. This information can then be used to assess whether an intention-to-treat analysis has been conducted.


 * Imputation:** Imputation is the substitution of some value for missing data. There are many different methods of imputing data, but all are associated with pros and cons, and there is no technique that is the best for all situations. Some guidance for deciding which method to use can be found at: www.missingdata.org.uk. Techniques include:
 * Logic: missing value is deduced from edit rules
 * Mean: missing value is replaced by the mean of the respondents
 * Ratio: missing value is replaced by the adjusted value of another variable
 * Previous value (//last observation carried forward//): missing value is replaced by the value declared at the previous occasion
 * Unit trend: missing value is replaced by the value declared at the previous occasion, but adjusted according to the trend of the unit
 * Group trend: missing value is replaced by the value declared at the previous occasion, but adjusted according to a group trend
 * Regression: missing value is replaced by other variables' adjusted values
 * Imputation using a model: missing value is replaced by a value predicted using a model adjusted on the respondents
 * Hot-deck: missing value is replaced by a randomly chosen value from the respondents in the current file
 * Cold-deck: missing value is replaced by a randomly chosen value from the respondents in another file
 * Nearest neighbour: missing value is replaced by the nearest neighbour's value, according to a distance function based on one or more auxiliary variable
 * Imputation with residuals: missing value is replaced by a predicted value to which a randomly selected residual is added
 * Imputation with forced residuals: missing value is replaced by a predicted value to which a randomly selected residual is added but subject to constraints
 * Probability: in the case of (0,1) variables, the missing value is replaced by the probability of obtaining a value of 1
 * Nearest neighbour's trend: missing value is replaced by the value reported at a previous occasion modified according to the trend of the nearest neighbour
 * Nearest predicted value: missing value is replaced by the value which is nearest to the value predicted for the nonrespondent (hybrid method between model and donor imputation)
 * Logistic imputation followed by model imputation: logistic regression is used to determine the category and the missing value is replaced by a value predicted using a model adjusted on the respondents

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Selective outcome reporting

 * Appropriate means of reporting outcomes:**
 * The study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre-specified way
 * The study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre-specified

Outcome measure planning tool Trial registration resources (see below)

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Other sources of bias

 * Guidance for minimizing bias in **cluster randomized trials** and **cross-over trials**: Cochrane Handbook, Chapter 16: Special Topics in Statistics

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 * Trial Registration:** Since July 1, 2005, the International Committee of Medical Journal Editors (ICMJE) has endorsed prospective trial registration (ICMJE Statement). This includes registering all trials with a publicly available registry prior to participant enrollment. Registries accepted by the ICMJE include:
 * Australian New Zealand Clinical Trials Registry (ANZCTR)
 * Brazilian Clinical Trials Registry (ReBec)
 * Chinese Clinical Trial Registry (ChiCTR)
 * Clinical Research Information Service (CRiS), Republic of Korea
 * Clinical Trials Registry - India (CTRI)
 * Cuban Public Registry of Clinical Trials (RPCEC)
 * EU Clinical Trials Register (EU-CTR)
 * German Clinical Trials Register (DRKS)
 * Iranian Registry of Clinical Trials (IRCT)
 * Japan's UMIN-CTR
 * Pan African Clinical Trial Registry (PACTR)
 * Sri Lanka Clinical Trials Registry (SLCTR)
 * The Netherlands' Trialregister.nl
 * The United States' ClinicalTrials.gov
 * The International ISRCTN.org

The WHO maintains the International Clinical Trials Registry Platform (ICTRP), a searchable database of multiple registries. It also provides a useful overview of trial registration, including:

1) Why is trial registration important? 2) How to register a trial 3) Organizations with policies

The registry can be searched at: []. A pediatric search filter can be applied by using the "Advanced Search" option and checking the box that says "Search for clinical trials in children."

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