Intention To Treat Analysis Vs Per Protocol


Intention To Treat Analysis Vs Per Protocol
The Per-Protocol (PP) principle – While an analysis according to the ITT principle aims to preserve the original randomization and to avoid potential bias due to exclusion of patients, the aim of a per-protocol (PP) analysis is to identify a treatment effect which would occur under optimal conditions ; i.e.

any major protocol deviations (e.g. intake of a concomitant medication affecting the primary endpoint) non-availability of measurements of the primary endpoint non-sufficient exposure to study treatment

There might be further criteria for selecting a PP population; however, the following approaches are essential:

The assignment to the PP analysis set needs to take place prior to the analysis (if possible in a blinded manner). Deviations that might be affected by the actual treatment should not be used as exclusion criteria: e.g., “premature discontinuation from the study” might not be a good choice of criterion for exclusion from the PP analysis, if this discontinuation was due to lack of efficacy (and therefore associated with the treatment received).

Both approaches, the ITT and the PP approach, are valid but have different roles in the analysis of clinical studies. Let’s come back to the question at the beginning of this article: What is worse, scenario A (claim a non-existing effect) or B (neglect an existing effect)? To answer this, consider the essential difference between the two cases: Case A means that a statistically proven result is actually wrong – a result that might cause dangerous effects.

  1. Based on such a proof, an inefficacious treatment might be approved and patients put into danger.
  2. Situation B on the other hand means that efficacy was not proven but also not refused,
  3. However, the non-proven efficacy does not equal a proven inefficacy! From a scientific perspective, such a non-decision has less implications than a wrong proof.

Therefore, in clinical trials situation A (also known as type I error ) is strictly controlled via a low pre-defined level of significance: a level of 5% e.g. says that (if there is actually no effect) the probability of situation A is only 5% or less.

  • Situation B (known as type II error ) on the other hand, is controlled via a meaningful sample size calculation, but usually with a less strict criterion (e.g.20%).
  • Concluding, it is more essential to avoid a wrong proof than to avoid a wrong non-decision (which is also bad, but A is worse).
  • Consequently, it is essential to keep the probability of situation A below the level of significance (e.g.5%).

Thus, the common rule for clinical trial analyses is: be conservative! While “conservative” means: do not increase the probability of a type I error !

What is on protocol or intention-to-treat analysis?

Abstract – Clinicians, institutions, and policy makers use results from randomized controlled trials to make decisions regarding therapeutic interventions for their patients and populations. Knowing the effect the intervention has on patients in clinical trials is critical for making both individual patient as well as population-based decisions.

  1. However, patients in clinical trials do not always adhere to the protocol.
  2. Excluding patients from the analysis who violated the research protocol (did not get their intended treatment) can have significant implications that impact the results and analysis of a study.
  3. Intention-to-treat analysis is a method for analyzing results in a prospective randomized study where all participants who are randomized are included in the statistical analysis and analyzed according to the group they were originally assigned, regardless of what treatment (if any) they received.

This method allows the investigator (or consumer of the medical literature) to draw accurate (unbiased) conclusions regarding the effectiveness of an intervention. This method preserves the benefits of randomization, which cannot be assumed when using other methods of analysis.

The risk of bias is increased whenever treatment groups are not analyzed according to the group to which they were originally assigned. If an intervention is truly effective (truth), an intention-to-treat analysis will provide an unbiased estimate of the efficacy of the intervention at the level of adherence in the study.

This article will review the “intention-to-treat” principle and its converse, “per-protocol” analysis, and illustrate how using the wrong method of analysis can lead to a significantly biased assessment of the effectiveness of an intervention. The most effective way to establish a causal relationship between an intervention and outcome is through a randomized controlled trial (RCT) study design.1 – 3 Randomization affords an unbiased comparison between groups as it controls for both known and unknown confounding variables.

  • If done correctly, randomization yields groups that are balanced with regard to prognostic variables (variables that have an impact or an influence on developing the outcome under study).
  • If two (or more) groups are prognostically balanced, with the exception of the intervention, and an investigator observes a difference in outcomes, a sound argument can be made attributing the difference in result to the intervention under study.
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Although recognized as the “gold standard” study design for establishing a causal relationship between intervention and outcome, the process of randomization alone does not wholly guard against bias. Incorrect analysis of the data can introduce bias even in the setting of the correct implementation of a valid random allocation sequence.

  1. It is therefore important to preserve the integrity of randomization during the implementation of the study and in analysis.
  2. One such way investigators and consumers of the medical literature may arrive at an incorrect and biased assessment of results is by failing to evaluate patients according to the group to which they were originally assigned.

Anything that disrupts the prognostic balance afforded by randomization introduces bias into the study and analysis. Therefore, the goal of the investigator is to preserve this prognostic balance throughout the entire study, including the analysis phase after all data and outcomes have been recorded.

What is the difference between per protocol analysis and complete case analysis?

Discussion – We have summarized the recommended approaches for how systematic review authors may handle MPD when conducting a meta-analysis. All general approaches recommend complete case analysis as the primary analysis. They also recommend additional sensitivity analyses using different imputation methods, mainly to assess the risk of bias associated with MPD.

  1. A commonly suggested approach is basing the imputation on the risk observed among followed up participants.
  2. Fewer approaches suggest taking uncertainty into account.
  3. This is the first systematic survey addressing recommendations for the handling MPD in systematic reviews that we are aware of.
  4. Major strengths include explicit eligibility criteria, an exhaustive search, and systematic approaches to study selection, data abstraction, and data synthesis.

One limitation of the review is the exclusion of non-English studies. Although focusing on English studies might lead to the loss of an appreciable number of eligible studies in clinical systematic reviews, this may be less of an issue for systematic surveys.

The different proposed approaches for dealing with missing participant data have advantages and disadvantages. The one proposed by Gamble and Hollis is the only one that has been tested using a simulation study. The approaches proposed by Higgins et al. and by Mavridis et al. relate the imputed odds of the outcome to its observed odds.

The approach proposed by Akl et al. relates the imputed incidence of the outcome to its observed incidence and proposes a way to assess risk of bias associated with missing data. The different analytical methods included in the above approaches have their own advantages and disadvantages.

The complete case analysis method does not involve any imputations, making it the preferred choice in the main analysis. However, it typically results in loss in power, and it assumes that the missingness is due to reasons not related to the characteristics of these participants nor to the outcome of interest (missing completely at random assumption), The best-case scenario and worst-case scenario methods represent implausible assumptions and cannot be used in the main analysis. However, the worst-case scenario might be useful in judging that the risk of bias associated with missing participant data as low, if its results (in a sensitivity analysis) do not substantially differ from those of the main analysis, Imputations using the informative missingness odds ratio (IMOR) and the RI LTFU/FU have the advantage of basing the imputations on observed events. This makes their use reasonable when conducting sensitivity analyses to judge risk of bias associated with missing participant data. The main challenge is in determining the plausible values for these ratios. Any of the above imputations will increase the count of events and consequently narrow the confidence intervals of the effect estimate, implying increased certainty. However, this is misleading as the narrower confidence interval is based on imputed data. This makes the analytical method to handle uncertainty important to apply when using any of the above imputation methods.

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We are not aware of rigorous studies evaluating or comparing different approaches and analytical methods of handling MPD in systematic review. While a large number of such studies have been published for trials, their results do not directly inform the approach for systematic reviews.

  • While trialists can use individual participant data to apply advanced statistical techniques such as multiple imputations, systematic reviewers can only use group level data with their inherent limitation, except in the case of individual participant data meta-analyses.
  • It is important to note the difference between a complete case analysis and per protocol analysis.

Complete case analysis is intended to deal with the problem of participants with missing outcome data while per protocol analysis is intended to deal with the problem of non-compliant participants. The complete case analysis includes only participants with available outcome data.

  • Per protocol analysis includes only participants who were compliant with the study protocol.
  • The use of one analysis is independent of the use of the other.
  • Indeed, Alshurafa et al.
  • Call for dealing with these two issues separately,
  • While the Cochrane Collaboration’s software (RevMan) does not include a module to account for missing data in meta-analysis, STATA has one for dichotomous data,

The “metamiss” command allows a complete case analysis as well as analyses applying a range of assumptions about the outcomes of participants with missing data, It also applies the Gamble-Hollis analysis, which inflates the pooled effect estimate to reflect the uncertainty associated with missing data.

Other software may have similar modules. While the approaches we have identified require further testing, they may guide review authors facing missing participant data in their analysis. Systematic reviewers should also aim to minimize MPD by contacting the trialists to obtain unpublished but available data.

In the unlikely case where trialists publish the outcomes of participants excluded from the trial analysis, the systematic reviewers may analyze them in the groups to which they were randomized. The approaches presented in this systematic survey do require further empirical assessment.

  • Indeed none of the imputation methods (including IMOR and RI) have been validated.
  • Assessment could include simulation studies assessing the performance of the different approaches for handling MPD when conducting a meta-analysis, in relation to the truth,
  • Assessment could also compare the effect of the different approaches on pooled effect estimates, when applied to a sample of published systematic reviews.

The findings of those investigations could then form the basis for consensus guidance on reporting, dealing with, and judging risk of bias associated with missing participant data in meta-analyses of randomized trials.

What is per protocol analysis in clinical trials?

Journal List CMAJ v.183(6); 2011 Apr 5 PMC3071397

As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more about our disclaimer. CMAJ.2011 Apr 5; 183(6): 696.

I congratulate CMAJ and Boutis and colleagues for a brilliant research paper.1 Intention-to-treat analysis is a comparison of the treatment groups that includes all patients as originally allocated after randomization. This is the recommended method in superiority trials to avoid any bias. For missing observations, “last value carried forward” is the recommended method.

Per-protocol analysis is a comparison of treatment groups that includes only those patients who completed the treatment originally allocated. If done alone, this analysis leads to bias. In noninferiority trials, both intention to treat and per-protocol analysis are recommended; both approaches should support noninferiority.

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In the article by Boutin and colleagues, intention to treat should have included 50 patients in either group as per randomization or at least 45 in the group with splints (in 4 patients, the diagnosis was wrong) and 50 in the group with casts; this may change the results to indicate a borderline effect.

In that article, the analysis was done with 43 patients in the splint group and 49 in the cast group, which appears to be a per-protocol analysis, though it was called an intention-to-treat analysis. Hence, noninferiority can be concluded only after analysis by both approaches.

What are the types of protocol analysis?

Type of Protocol Analyzer: – Industry has two types of protocol analyzer. Hardware protocol analyzer and software protocol analyzer. Hardware protocol analyzer : The hardware based protocol analyzer uses hardware and software to capture the packets. Hardware based protocol analyzer are used to debug hardware and complex SoC protocol interfaces.

  1. The hardware based protocol analyzer captures the packets of the interfaces for downstream analysis.
  2. Some of the common hardware based protocol analyzer are UFS protocol analyzer, eMMC protocol analyzer, PCIe protocol analyzer.
  3. Software protocol analyzer: Software based protocol analyzer use only software to capture and analyze the protocol.

These are commonly known as network analyzers. The software protocol analyzer is used for capture and analysis of LAN,Wireless network etc.

What is meant by protocol in treatment?

(PROH-tuh-KOL) A detailed plan of a scientific or medical experiment, treatment, or procedure. In clinical trials, it states what the study will do, how it will be done, and why it is being done.

Is a clinical investigation plan the same as a protocol?

Clinical Investigation Plan – The Clinical Investigation Plan (CIP) is the key document in device trials; it is effectively the equivalent of the protocol in a clinical trial. The CIP is defined as follows ( ISO, 2003, p.6 ): The CIP shall be a document developed by the sponsor and the clinical investigator(s).

What are the advantages of intention-to-treat analysis?

Intention-to-treat analysis (ITT) analyses are often used to assess clinical effectiveness because they mirror actual practice, when not everyone adheres to the treatment, and the treatment people have may be changed according to how their condition responds to it.

What is the meaning of as per protocol?

n 1 the formal etiquette and code of behaviour, precedence, and procedure for state and diplomatic ceremonies 2 a memorandum or record of an agreement, esp. one reached in international negotiations, a meeting, etc. a an amendment to a treaty or convention b an annexe appended to a treaty to deal with subsidiary matters or to render the treaty more lucid c a formal international agreement or understanding on some matter 4 (Philosophy, In full) protocol statement a statement that is immediately verifiable by experience See → logical positivism 5 (Computing) the set form in which data must be presented for handling by a particular computer configuration, esp.

in the transmission of information between different computer systems (C16: from Medieval Latin protocollum, from Late Greek protokollon sheet glued to the front of a manuscript, from proto- + kolla glue) Geneva protocol n the agreement in 1925 to ban the use of asphyxiating, poisonous, or other gases in war.

It does not ban the development or manufacture of such gases English Collins Dictionary – English Definition & Thesaurus Collaborative Dictionary English Definition

rpm n. round per minute Used for the rotational speed of gramophone records. Ex. : “45 rpm”, “33 rpm”, “78 rpm”.
obscurum per obscurius exp. a mystery wrapped in an enigma Latin phrase meaning “to explain an obscurity by something still more obscure”
arpu abbr. acron. average revenue per user ;; acronym
break down silos exp. (in an organization) set up a more informal structure/workflow/environment; give up on communication protocols between departments

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What is meant by protocol in treatment?

(PROH-tuh-KOL) A detailed plan of a scientific or medical experiment, treatment, or procedure. In clinical trials, it states what the study will do, how it will be done, and why it is being done.