Decision makers in the healthcare field like doctors, patients and policy makers need access to clinical evidence to address issues that have bearing on the health of the population and the treatment prescribed and thereby on the financials implications of the healthcare industry.
Let’s check out what the cancer statistics are before we look at why observational research can be important for clinical decision making.
According to the Statistics provided by the National Cancer Institute
However, the most recent SEER Cancer Statistics Review , updated in September 2016, shows that cancer death rate decreased by:
As the overall cancer death rate has declined, the number of cancer survivors has thereof increased. Thus, these figures do indicate that some progress is being made against the disease. Based on their studies, although rates of smoking, a major cause of cancer, indicate a decrease, the U.S. population is stated to be aging, and cancer rates are known to increase with age. Obesity, another risk factor for cancer, is also showing an increasing trend, even among youngsters. So what exactly is happening? At one glance statistics informs us that cancer death rates are decreasing, and yet if we take into account lifestyles changes that are factors leading up to cancer, what can one derive from such statistics, especially among the chronic diseases like cancer?
Are the awareness programs on diagnosing and catching the disease early to begin preventive treatment the reason for the decline or is a more aggressive treatment based on observational research that is impacting clinical decision making the reason? Or could a mix of the two be making the change?
Observational research is known to help address issues that are otherwise difficult or impossible to study. Observational research is known to extend the knowledge base beyond the clinical trial setting and thus capture a more accurate picture of everyday clinical practice, particularly patients’ experiences of long-term chronic disease treatment.
Currently, observational data are used routinely to inform parameters in economic models such as the underlying rate of disease progression. There is now increasing interest in using observational data to inform estimates of treatment effect. Although, observational analyses are known to be at increased risk of bias, decision-makers need to be cautious and thereof require analytical techniques that minimize this risk. Decision-makers also need to be able to make an accurate assessment of the likely extent of bias and its impact on decision uncertainty
Randomized Controlled Trials (RCT) is a study in which people are allocated at random (by chance alone) to receive one of several clinical interventions. One of these interventions is the standard of comparison or control. Randomization trials are most often able to balance out unmeasured differences between the groups being compared. On the other hand, observational studies have to control for differences between individuals, and thus they cannot provide the same level of evidence to guide clinical decision making. According to BCRF researcher Dr. Visvanathan, “The care a patient receives during and after cancer is based on clinical evidence obtained through precisely conducted clinical trials known as randomized controlled trials (RCT).”
Although, both, Randomized controlled trials (RCTs) and observational studies are known to provide valuable insights into the management of chronic diseases like cancer, there are inherent limitations on RCTs that can affect the validity of clinical trial outcomes. But, can observational studies alone impact clinical decision making? And does Observational research have the potential to do so?
A recent report by the American Society of Clinical Oncology (ASCO) has highlighted the untapped potential of observational research to augment clinical trial results to better inform clinical decision thus enhancing the value of observational studies as a complement to clinical trial data for clinical decision. It has been observed only by using well-structured observational studies can our understanding of the translation of clinical trials into clinical practice be improved.
It should be understood that many clinical situations can only be evaluated by using observational studies, albeit more susceptible to bias and errors. This then underlines the need for surgeons to become more familiar with the alternatives to RCTs. Understanding principles of observational epidemiology will not only help to exercise critical appraisal of research reports but also guide to design and execute studies that can have far reaching impact on the treatment of oncology. The authors of the report, (Journal of Clinical Oncology by Visvanathan et al ) conclude that, “The knowledge gained from observational studies will help the cancer care community reach its goal of providing high-quality, evidence-based care to all patients with cancer.”
