REAL WORLD DATA (RWD) AND REAL WORLD EVIDENCE (RWE)

What are RWD and where do they come from?

Real world data are the data relating to patient health status and the delivery of health care routinely collected from a variety of sources.
RWD can come from a number of sources ,for example

• electronic health records
• claims and billing activities
• product and disease registries
• patient generated data including in home up settings

What is RWE?

Real world evidence is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD.RWE can be generated by different study designs or analysis , including randomized trials, including large trials and observational studies ( prospective and retrospective).

what is the importance of RWE ?

RWE is important because it provides information about how a treatment works outside of a clinical trial for example ,if a randomized controlled trial (RCT ) demonstrate that a particular drug lower blood pressure in hypertensive patients but there are no related
studies on this topic , any conclusions drawn from the findings of the study may be inappropriate for all antihypertensive patients.

RWE vs RCTs

Randomized clinical trials (RCTs) are initial studies conducted to establish the safety and efficacy of an investigational product. RCTs are designed to focus on internal validity (capability of a clinical study to provide reliable results which are actually true and not due to an error), which may sometimes compromise generalizability to general population. RCTs are conducted on very selective populations, so patients with comorbidities may be excluded. Furthermore, these studies are conducted in very controlled settings. Most of the clinical treatment guidelines are formulated based on the RCT results. However, these results do not truly represent the actual entire population, since these RCTs have many inclusion and exclusion criteria. Hence, these results from RCT require support from diverse situations that would be present in a real-world clinical scenario.

Advantage of RWE Compared with RCTs

As compared to RCT, depending on the type of RWE, it may take much less time, less resources, and less cost. In RWE studies, data can be accessed rapidly and data can be retrieved easily. RWE studies can be used to evaluate the natural history of disease, prevalence, incidence, unmet medical need, current treatment patterns, and standard of care. RWE studies can be used to support patient outcomes and health economics. RWE studies can be used to understand current health-care services.
Research which is not possible with RCT can be done with RWE, for example, studies on high-risk groups, Side effects which are less frequently seen can be studied better with a RWE study as compared to RCT since RCT is conducted in a smaller population and with a shorter duration.

Examples for RWE 

Retrospective study: This is a retrospective study done to evaluate to what extent type 1 diabetic guidelines are followed in clinical practice in Sweden. These guidelines recommend quarterly or more frequent hemoglobin A1c (HbA1c) assessments in patients with uncontrolled type 1 diabetes mellitus. 5989 patients were recruited from 10 outpatient diabetes clinics in Sweden. Diab-Base electronic medical record database was used for data collection. Data on patient characteristics, including treatment, general risk factors for diabetic complications, and frequency of HbA1c measurements, were retrieved for all patients. This study provided important insight into HbA1c measurement in routine clinical practice in Sweden. It was found that the measurements were done less than that recommended by guidelines recommend.

Prospective study: LANDMARC study is a prospective, multicenter study evaluating a large cohort of people with type 2 diabetes mellitus across India over a period of 3 years. This study will reveal the trends in complications associated with diabetes; treatment strategies used by physicians; and correlation among treatment, control, and complications of diabetes.

Cross-sectional study: This multicenter study was designed to determine the control of dyslipidemia in the Indian diabetic population treated with lipid-lowering drugs. The study was conducted in 178 sites in India. This study found that dyslipidemia control in Indian type 2 diabetes mellitus patients is very poor with almost half of them not reaching their low-density lipoprotein- cholesterol goal.

References

1. Framework for FDA’s Real-World Evidence Program. US: Food and Drugs Administration; 2018. [Google Scholar]
2. Bhatt A. Conducting real-world evidence studies in India. Perspect Clin Res. 2019;10:51–6. [PMC free article] [PubMed] [Google Scholar]
3. Kim HS, Lee S, Kim JH. Real-world evidence versus randomized controlled trial: Clinical research based on electronic medical records. J Korean Med Sci. 2018;33:e213. [PMC free article] [PubMed] [Google Scholar]
4. Monti S, Grosso V, Todoerti M, Caporali R. Randomized controlled trials and real-world data: Differences and similarities to untangle literature data. Rheumatology. 2018;57:vii54–8. [PubMed] [Google Scholar]
5. National Academies of Sciences. Engineering, and Medicine; Health and Medicine Division; Board on Health Sciences Policy; Forum on Drug Discovery, Development, and Translation. Real. World Evidence Generation and Evaluation of Therapeutics: Proceedings of a Workshop. 3, Opportunities for Real-World Data. Washington (DC): National Academies Press (US); 2017. Feb 15, [Last accessed on 2021 Jan 12]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK441694/ [Google Scholar]
6. European Medicines Agency. Observational Data (Real World Data). European Medicines Agency. 2017 [Google Scholar]
7. US Food and Drug’s Administration. Real World Evidence. [Last accessed on 2021 Jan 20]. Available from: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence .
8. Makady A, de Boer A, Hillege H, Klungel O, Goettsch W. What is real-world data? A review of definitions based on literature and stakeholder interviews. Value Health. 2017;20:858–65. [PubMed] [Google Scholar]

9. Matuleviciene V, Attvall S, Ekelund M, Clements M, Dahlqvist S, Fahlén M, et al. A retrospective study in 5,989 patients with type 1 diabetes in 10 outpatient diabetes clinics in Sweden of the frequency of measuring HbA1c in clinical practice. J Diabetes Metab. 2014;5:5. [Google Scholar]
10. Das AK, Mithal A, Kumar KM, Unnikrishnan AG, Kalra S, Thacker H, et al. Rationale, study design and methodology of the LANDMARC trial: A 3-year, pan-India, prospective, longitudinal study to assess management and real-world outcomes of diabetes mellitus. Diabet Med. 2020;37:885–92. [PMC free article] [PubMed] [Google Scholar]
11. Mithal A, Majhi D, Shunmugavelu M, Talwarkar PG, Vasnawala H, Raza AS. Prevalence of dyslipidemia in adult Indian diabetic patients: A cross sectional study (SOLID) Indian J Endocrinol Metab. 2014;18:642–7. [PMC free article] [PubMed] [Google Scholar]
12. Rajivlochan M. Clinical audits and the state of record keeping in India. Ann Neurosci. 2015;22:197–8. [PMC free article] [PubMed] [Google Scholar