This study did not show that mometasone and hydrocortisone have similar atrophogenic potential, nor did it show a dissociation of potency from safety. Indeed, the design of this trial was such that efficacy differences between the 2 treatments were detected, but differences in the rate of adverse events which occur uncommonly , even ones that are clinically significant, were not apparent.
A recent study compared the efficacy of once-daily vs twice-daily application of betamethasone valerate in a foam vehicle Luxiq; Connetics Corporation, Palo Alto, Calif for the treatment of scalp psoriasis. Patients were evaluated at 0 and 4 weeks by a blinded physician grader who graded the scalp for signs and symptoms of psoriasis. There was a statistically significant decrease in erythema and plaque thickness with both once-daily dosing and twice-daily dosing.
While the sample size was adequate to determine that both treatments were efficacious, a larger sample size or longer duration of follow-up in this trial was needed to demonstrate a meaningful difference in efficacy between once- and twice-daily dosing. In a study of treatment of herpes labialis with penciclovir cream, patients were enrolled in a double-blind, placebo-controlled trial to compare the safety and efficacy of topical penciclovir in the treatment of recurrent cold sores.
There was a statistically significant decrease in healing time as well as a shorter time to loss of pain and viral shedding in penciclovir-treated patients than among patients who applied the vehicle control. Healing of lesions in the treatment group occurred in a median of 4. The authors also stated that pain median duration, 3. The hazard ratios for pain and viral shedding for those patients who used penciclovir cream were greater than 1, which indicated a greater risk for developing the mentioned effects.
However, the results of this study, 8 while statistically significant, lack much clinical relevance. This study, by using a very large sample size, detected a difference so small that it is probably not of much clinical benefit to patients.
This is an instance of a study using too high a power, thus allowing the detection of a very slight difference. Studies such as these, while apparently well designed and executed, make it imperative that the reader determine what he or she considers to be of clinical value.
Looking at small differences in the time to clearing is not likely to be very relevant clinically. Another approach would be to choose a clinically relevant measure of success and compare the success rates between the drug and placebo groups. The use of topical minoxidil for the treatment of early male pattern baldness is another example of a study with statistical significance but limited clinical utility.
The hair count difference did not appear to be clinically significant in that there was no difference in subjective cosmetic assessment between the treatment groups. There are new diagnostic technologies constantly surfacing in dermatology, each hoping to deliver results superior to those of the current tools. However, as exciting as each new discovery may be, it is essential to temper our optimism by remembering that some of these new tests might never be adequately evaluated for statistical significance.
The incidences of the disorders they seek to detect are sometimes so rare that it would be almost impossible to find a sample population large enough to attain statistically significant results. For example, dermoscopy is reported to deliver more sensitivity and specificity than clinical examination alone in evaluating a patient for melanoma and the need to perform a biopsy.
The sensitivity of a dermatologist in detecting a melanoma is very high. Assuming that 1 in 10 persons with suspect nevi canvassed for study enrollment actually had melanoma, more than subjects would need to be canvassed. Such a study size would be difficult though not impossible to achieve, and obviously even more subjects would be needed if fewer than 1 in 10 had a true melanoma. While there may be good reasons to use dermoscopy, careful clinical examination and a low threshold for biopsy are already very good screening tools for melanoma, and it will be quite difficult to show that dermoscopy is better.
Similarly, consider the issue of collagen propeptide blood tests in the detection of liver disease in patients treated with methotrexate. Clinical trials tend to illustrate the relative performance of interventions in populations, not individuals. The data are usually presented as mean values with an index of variability SD, SE, CV for end-of-trial absolute or between-treatment differences in predefined endpoints. We mistakenly perceive the mean effect as the effect. It is therefore possible that small-but-significant differences in the overall mean values disguise much larger clinically valuable effects in limited subgroups.
The chances are the original study would not be powered to show a statistically significant difference for this subgroup, but post hoc subgroup analyses could nevertheless inform the direction to take with future studies. In terms of marketer of the intervention, this possibility poses a dilemma: The identification of the subgroup s in which the intervention is really advantageous effectively niches the product.
Does the marketeer prefer a narrative that describes a small benefit for the many, or a large benefit for the few? Clearly, prescribers, regulators, payers and patients will ultimately benefit from tailored intervention informed by subgroup analysis. Thank you! I am not agree with all aurguments presented here. Whenever, statistical significance and clinical or scientific significance are not equivalent then you need to assess your study or experimental settings for scientific validations again.
Increasing sample size can not convert non-significance into significance. And what you said in you article like cost and other thing that are not included in your study or experiment.
At what cost costomers might buy the drug need statistical study but it will be more a business problem. A good article. Also great comments. The issue of statistical significance and clinical significance has generated a lot constructive arguments at different level of biomedical researches, as we can also see here. But the fact is that statistical significance cannot be wholly accepted as clinical significance. You can agree with me that statistical significance is a necessary condition but not a sufficient condition for clinical significance.
Evidence-based medicine is the new god. Nothing replaces common sense and logic … or does it? I agree with what is clinically relevant, it makes sense. This ability of making challenging subjects , easy to understand will certainly make you a much in demand and popular professor in the future. Stay on your journey and you will be an amazing physician. Select Your State - Outside of U. Clinical Significance Statistical Significance Definition In medical terms, clinical significance also known as practical significance is assigned to a result where a course of treatment has had genuine and quantifiable effects.
Broadly speaking, statistical significance is assigned to a result when an event is found to be unlikely to have occurred by chance. This could include the correlation between two variables, the mean difference between two variables, or the risk of a particular event happening. The number needed to treat NNT is a type of effect size that measures the average number of patients who need to be treated to prevent one additional bad outcome, or the number who need to be treated for one to benefit over the control.
Participants are also scored into categories for deteriorated, unchanged, improved, and recovered. The significance level of a study is set in advance, before data is collected. Originally, it was defined as 0. If, after all data is collected, The p-value is less than or equal to the significance level, the results are said to be statistically significant.
History Historically, clinical significance has been applied primarily in pharmaceutical trials and medical research. But it also has use in non-medical settings, too, where it can provide a more rigorous critique of a data set.
It can also be useful in the early stages of pharmaceutical testing to determine whether further research is warranted. Examples A pharmaceutical company is testing the efficacy of a new anti-pain drug with clinical trials. It cultivates a representative participant group, gauges their pre-test pain levels, and then closely monitors their progression, before recording their post-test pain levels.
E-mail: moc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3. This article has been cited by other articles in PMC. Abstract In clinical research, study results, which are statistically significant are often interpreted as being clinically important.
Keywords: Biostatistics, confidence intervals, data interpretation, statistical. Footnotes Source of Support: Nil. LeFort SM. The statistical versus clinical significance debate.
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