The various types of study design are described below in descending order of strength:

1. Randomized controlled clinical trials.
   1. Double-blinded.
   2. Nonblinded treatment delivery.

   The randomized, double-blinded controlled clinical trial (1i) is the gold standard of study design. To achieve this ranking, the study allocation must be blinded to the physician both before and after the randomization and the treatment assignment take place. This design provides protection from allocation bias by the investigator and from bias in assessment of outcomes by both the investigator and the patient. Unfortunately, most clinical trials in oncology cannot be double-blinded after treatment allocation because procedures or toxic effects often vary substantially among study allocations in ways that are obvious to both the health care professional and the patient. In most cases, however, it should be possible to blind the investigator and the patient until the randomization has been made. If blinding of the therapy delivered cannot be accomplished, a rank of 1ii is assigned.

   Meta-analyses of randomized studies offer a quantitative synthesis of previously conducted studies. The strength of evidence from a meta-analysis is based on the quality of the conduct of individual studies. Moreover, meta-analyses can magnify small systematic errors in individual studies. A study comparing the results of single large randomized trials to those of meta-analyses of smaller trials published earlier on the same topics showed only fair agreement (kappa statistic = 0.35). Outcomes of the large randomized controlled trials were not predicted accurately by the meta-analysis 35% of the time.[1,2] Meta-analyses performed by different investigators to address the same clinical issue can reach contradictory conclusions.[2] Therefore, meta-analyses of randomized studies are placed in the same category of strength of evidence as are randomized studies, not at a higher level.

   Subset analyses of randomized studies are subject to errors inherent in multiplicity (i.e., statistically significant results to be expected as a result of random variation of measured effects in multiple subsets). Therefore, subset analyses do not represent the same strength of evidence as the overall analysis of a randomized trial as designed unless explicit prospective hypotheses are made for the analyzed subset. Otherwise, subset analyses should be placed in the next lower category of study design (nonrandomized controlled clinical trials).




2. Nonrandomized controlled clinical trials.

   This category includes trials in which treatment allocation was made by birth date, chart number, day of clinic appointment, bed availability, or any other strategy that would make the allocation known to the investigator before informed consent is obtained from the patient. An imbalance can occur in treatment allocation under such circumstances. For the reasons given above, subset analyses within randomized trials often fall into this category of evidence.




3. Case series.
   1. Population-based, consecutive series.
   2. Consecutive cases (not population-based).
   3. Nonconsecutive cases.

   These clinical experiences are the weakest form of study design, but they may be the only available or practical information in support of a therapeutic strategy, especially in the case of rare diseases or when the evolution of the therapy predates the common use of randomized study designs in medical practice. They may also provide the only practical design when treatments in study arms are radically different (e.g., amputation vs. limb-sparing surgery). Nevertheless, these experiences do not have internal controls and must therefore look to outside experiences for comparison. This always raises the issues of patient selection and comparability with other populations. In order of generalizability to other populations are population-based series, nonpopulation-based but consecutive series, and nonconsecutive cases.

References

1. LeLorier J, Grégoire G, Benhaddad A, et al.: Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N Engl J Med 337 (8): 536-42, 1997.  [PUBMED Abstract]
   
   
2. Bailar JC 3rd: The promise and problems of meta-analysis. N Engl J Med 337 (8): 559-61, 1997.  [PUBMED Abstract]
   
   

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