Most clinicians, physicians, researchers, and others are up against a huge challenge — the overwhelming wealth of information, even in taut, small areas of speciality interest. Reviews designed to summarise the outsized volumes of information are, as a result, frequently published. When a review is done systematically, following certain criteria and the results are pooled and analysed quantitatively, it becomes meta-analysis.
A well-designed meta-analysis not only provides valuable information for researchers, clinicians, pharmaceutical industry, and others, including policy-makers, but also a host of decisive caveats in performing and interpreting them to the best extent possible.
So far, so good. Yet, a major limitation continues to haunt the scientific community. Meta-analysis is not a panacea. It is, at best, a valuable ‘remedy.’ This is, all the same, more than half of the battle won. Meta-analysis is well-established in medicine, all right — although the whole idea got its first major boost in the social and behavioural sciences. This was primarily because of the presence of a large number of confounding factors capable of disproving a tentative claim.
To paraphrase Dr Erick H Turner, MD, a researcher who analysed the publication status of studies of antidepressants. “Based on studies registered with the US Food and Drug Administration [FDA], [we] found that 97 per cent of the positive studies were published versus only 12 per cent of negative studies. Furthermore, when the non-published studies were not included in the analysis, the positive effects of individual drugs increased between 11 per cent and 69 per cent.” “One reason for the publication bias,” as Dr Turner explained, “is that drug manufacturers are not generally interested in publishing negative studies… Yet another [factor] may be that [medical journal] editors favour positive studies, because they are the ones that make headlines and give the publication visibility.”
Yet, there is a huge upside. Take for instance, the meta-analysis on aspirin and other anti-coagulant drugs, in the 1970s, which provided the ‘prop’ for the efficacy of the former, when taken together with the latter. It took just two years for the US Food and Drug Administration [FDA], thereafter, to approve the use of aspirin for survivors of myocardial infarction. You guessed it right. If only the use of meta-analysis for aspirin was established a good 25 years before, it could have saved over 15,000 lives, every year, in the US alone.
The use of meta-analysis in medicine during the last few years has certainly brought about a welcome transformation. It has also, in fact, brought an end to many medicinal- or drug-propelled ‘slam-bang’ effects. This is because the future of medicine is enormously keyed to seeking new agents with incremental benefits, safety, and therapeutic effects. If this is not a ‘signal proof,’ or the whole essence of meta-analysis, what is?
To pick another typical example—the meta-analysis on the therapeutic effectiveness of streptokinase in heart attack. This is how it all happened and emerged — nearly eight previous studies did not significantly confirm the drug’s beneficial effects. Conversely, a meta-analysis conducted in the US, showed that streptokinase lowered death rates for patients treated immediately after symptoms of a heart attack occurred. This was a shot in the arm. The streptokinase perestroika exemplified the promise the potent antioxidant, coenzyme Q10 [CoQ10], holds as a supplement in the management of hypertension — a ‘solid ground’ for meta-analysis, including the ‘big leap’ to exploring new theories to deciphering and analysing possibilities and variations between subject populations and also augmenting therapies in ways that would be next to impossible in just one isolated study — howsoever immaculate, or meticulous.
All said and done, meta-analysis has its share of critics. Detractors call it philosophical, or prejudiced, with its ‘hard’ and ‘soft’ end-points — or, publication bias, because studies that show ‘positive’ results — usually in favour of a new treatment, or against a well-established protocol — are more likely to be published than those that do not, as discussed earlier. On the realistic side too, there is a lurking ‘fall-out’ of meta-analysis — the ‘imprudent’ use of sub-group analysis, most often with computer assistance. Yet, despite its pitfalls, most scientific observers reckon that meta-analysis is the best there possibly is — and, that it is a definitive advance for better protocols to emerge in the future. This is also precisely how science expands and has expanded all along.
The big point, on the brighter side, is meta-analysis can help bring researchers, scientists, clinicians and physicians — as close as they can ever hope, wish, and also urge for — to arrive at the ‘absolute’ answers they relentlessly seek to their niggling questions and/or inquiry. Well, there is a ‘big ask’ too—if only science and medicine avoid the temptation to regard meta-analysis as a completely objective ‘question-emblem’ with solutions, they will, doubtless, find the methodology a prudent tool to detach the chaff from the grain and vice versa.
The reason is simple, also profound — science does not begin with a nice question, nor does it end with a nice answer.
