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While sequence generation discusses generation of an unpredictable sequence of assignments, it is of considerable importance to understand how the se- quence is applied when participants are enrolled into the trial. Multiple methods for allocation concealment have been described (Table 5). Allocation concealment should not be confused with blinding.

13.3.7 Implementation

In addition to knowing the methods used in con- cealment of the allocated intervention at the time of enrollment, it is also important to understand how the random sequence was implemented; specifically, who generated the allocation sequence, who enrolled the participants, and who assigned the participants to trial groups.

13.3.8 Blinding

Blinding refers to keeping study participants, healthcare providers, and assessors unaware of the assigned intervention. The trials may be open, single-

blind, or double-blind. Further, it is essential to know how the success of blinding was evaluated.

13.3.9 Statistical Methods

While data can be analyzed in many ways, it is es- sential to specify which statistical procedure was used for each analysis, and further clarification for each analysis. In addition, methods for additional analy- sis, such as subgroup analysis and adjusted analysis, should be reported. Thus, statistical methods are used to compare groups for primary outcome(s), specifying whether a 1- or 2-sided or CI approach was used.

13.4 Results

Results of a properly conducted randomized trial should include participant flow, method of recruit- ment, baseline data, numbers analyzed, outcomes and estimation, ancillary analysis, and adverse events. 13.4.1 Participant Flow

Participant flow is an extremely important part of the equation. Thus, it should be described in detail as shown in Figure 4. Occasionally, the design and execu- tion of some RCTs is straightforward, and the flow of participants through each phase of the study can be Table 13. Information required to document the flow of participants through each stage of a randomized, controlled trial.

Stage Number of People Included Number of People Not Included

or Excluded Rationale

Enrollment People evaluated for potential

enrollment People who did not meet the inclu-sion criteria People who met the inclusion criteria but declined to be enrolled

These counts indicate whether trial par- ticipants were likely to be representative of all patients seen; they are relevant to assessment of external validity only, and they are often not available

Randomization Participants randomly assigned Crucial count for defining trial size and assessing whether a trial has been ana- lyzed by intention to treat

Treatment

allocation Participants who received treatment as allocated, by study group Participants who did not receive treatment as allocated, by study group

Important counts for assessment of inter- nal validity and interpretation of results; reasons for not receiving treatment as allocated should be given

Follow-up Participants who completed treat- ment as allocated, by study group Participants who completed follow- up as planned, by study group

Participants who did not complete treatment as allocated, by study group

Participants who did not complete follow-up as planned, by study group

Important counts for assessment of inter- nal validity and interpretation of results; reasons for not completing treatment or follow-up should be given

Analysis Participants included in main analy-

sis, by study group Participants excluded from main analysis, by study group Crucial count for assessing whether a trial has been analyzed by intention to treat; reasons for excluding participants should be given

Source: Altman DG, et al. The revised CONSORT statement for reporting randomized trials: Explanation and elaboration. Ann Intern Med 2001; 134:663-694 (108).

described adequately in a few sentences. However, in more complex studies, it may be difficult to discern whether and why some participants did not receive the treatment as allocated, were lost to follow-up, or were excluded from the analysis (495). Table 13 shows the information required to document the flow of partici- pants through each stage of the RCT, through various stages of the study, starting from enrollment to data analysis, with the number of people included through various stages, and the number of people not included or excluded, along with the rationale for each action. The flow diagram may be expanded to describe treat- ment allocation or any other aspects and also other in- formation may be added (108).

A participant flow diagram and description also should describe protocol deviations from the study as planned, together with the reasons.

13.4.2 Numbers Analyzed

The number of participants in each group is an essential element of the results. Even though the flow diagram indicates the number of participants for whom outcomes were available, these numbers may vary for different outcome measures. Thus, the clear descriptions of the number of participants (denomina- tor in each group should be included in each analysis) and whether “intention-to-treat” and an alternative analysis were conducted should be reported. Further, the results should be stated in an absolute number when feasible (e.g., 30 of 60, not 50%). Failure to in- clude all participants may bias trial results. Most tri- als do not yield perfect data. Further, “protocol viola- tions” may occur, such as when patients do not receive the full intervention or the correct intervention or few ineligible patients are randomly allocated in error. 13.4.3 Recruitment

It is essential to describe when a study took place and over what period participants were recruited. It is also important to understand the rate at which par- ticipants were recruited. Medical and surgical thera- pies, including concurrent therapies, evolve continu- ously and may affect the routine care given to patients during a trial. Further, the length of follow-up, which is not always a fixed a period after randomization, must be shown with a median duration of follow- up (496,497). It is also important to report if the trial was stopped owing to the results of interim analysis of data, as early stopping will lead to a discrepancy between the planned and actual sample sizes. In ad-

dition, trials that stop early are likely to overestimate the treatment effect (498).

13.4.4 Baseline Data

Even though the eligibility criteria indicates who was eligible for the trial, it is also important to de- scribe the characteristics of participants who were ac- tually recruited. This information provides the impor- tance and clinical relevance of the trial. Generally RCTs aim to compare groups of participants that differ only with respect to intervention, thus maintaining similar baseline characteristics among the groups. While prop- er random assignment prevents selection bias, it does not guarantee that the groups are equivalent at base- line and any difference in baseline characteristics are, however, the result of chance rather than bias (222), in contrast to widely held misbeliefs (37). Baseline data are extremely valuable when the outcome measure can also be measured at the start of the trial. Baseline information should be presented efficiently for both groups. The variability of the data should be reported with average values and continuous variables can be summarized for each group by the mean and SD. If continuous data have an asymmetrical distribution, a preferable approach may be to quote the median and percentile range (25th and 75th percentiles) (431). However, standard errors and CIs are not appropriate for describing variability as they are inferential rather than descriptive characteristics.

Despite many warnings about their inappropri- ateness (221,222,499), significance tests of baseline differences are common and reported in 50% of the trials (108,439). The trial protocol and the result de- scription should state whether or not adjustment is made for nominated baseline variables by using AN- COVA (90,500).

13.4.5 Intention-to-Treat Analysis

The intention-to-treat strategy is commonly rec- ommended to handle such issues as protocol viola- tions and withdrawals to analyze all participants ac- cording to their original group assignment, regardless of what subsequently occurred. However, this is not always straightforward to implement. It is common for some patients not to complete a study – they may drop out or be withdrawn from active treatment – and thus are not assessed at the end. Even though those participants cannot be included in the analy- sis, it is customary still to refer to the analysis of all available participants as an intention-to-treat analysis.

However, the term is also used inappropriately when some participants for whom data are available are excluded; specifically, if the patients received none of the intended treatment because of non-adherence to the protocol, etc. Conversely, analysis can be restricted to only participants who fulfill the protocol in terms of eligibility, interventions, and outcome assessment. This analysis may be considered as per protocol analy- sis and may be compared with intention-to-treat anal- ysis. However, non-compliance with assigned therapy may mean that the intention-to-treat analysis under- estimates the real benefit of the treatment (501,502). Consequently, additional analysis may be considered. It has been reported that studies reporting an inten- tion-to-treat analysis were associated with some other aspects of good study design and reporting, such as describing a sample size calculation (503).

The inclusion of all subjects in intention-to-treat analyses regardless of their follow-up status requires investigators to deal with the resulting missing data by one of several approaches.