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Real World Evidence (RWE) 101 – Study Designs

RWE 101 – Study Designs

Real-world evidence (RWE) studies are becoming increasingly important in healthcare decision-making. There are various study designs used to generate RWE, each with their unique benefits:
 
[1] Cohort Studies: Cohort studies are observational in nature, where two or more groups (cohorts) distinguished by their exposure to a certain factor (like a medical treatment or lifestyle choice) are followed and assessed to determine the effect of that exposure. These studies are advantageous in studying rare outcomes, multiple outcomes, or outcomes that take a long time to develop.
 
[2] Case-Control Studies: These studies start with the outcome and then look backward to find the exposure. They’re efficient for studying rare diseases or diseases with a long latency period, as well as multiple exposures. However, they may not be as reliable as cohort studies due to potential recall bias.
 
[3] Cross-Sectional Studies (Prevalence Studies): These studies observe a defined population at a single point in time or time interval. They’re useful in understanding the burden of a disease in a population, assessing public health needs, and planning healthcare services.
 
[4] Registry-Based Studies: These are observational studies where data are collected prospectively or retrospectively for patients with a particular condition or who are undergoing a specific procedure. Registry-based studies provide long-term, real-life data about prognosis, adverse events, quality of life, and cost-effectiveness.
 
[5] Pragmatic Clinical Trials (PCTs): Unlike traditional randomized clinical trials, PCTs are designed to determine the effectiveness of interventions in real-world routine practice conditions. They often include a more diverse patient population, multiple care settings, and less rigid protocols.
 
[6] Retrospective Studies: This involves analyzing existing datasets (like EHRs or insurance claims databases) to find associations or trends. This is also known as secondary use of existing data. While these are generally quicker and less expensive, they are subject to the limitations of the existing data, which may not have been collected for research purposes.
 
[7] Prospective Observational Studies: In these studies, subjects are followed over time with data collected about various factors that might influence the outcome of interest. These studies are useful in understanding the natural history of disease and the effectiveness of different treatments in the real world. These studies usually include both secondary data (data collected for a different purpose) and primary data (data collected specifically for the purposes of the study).

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Real World Evidence (RWE) 101 – Study Designs2023-08-07T16:44:52+00:00

Real World Evidence (RWE) 101 – Protocol Considerations

RWE 101 – Protocol Considerations

Real-world evidence (RWE) study protocols and clinical trial protocols both outline the design and conduct of a study. However, they are distinctly different in several ways given the differences in objectives, methodologies, settings, and populations involved in clinical trials versus RWE studies.
 
[1] Objectives: The main objective of a clinical trial is to evaluate the efficacy and safety of a medical intervention in a controlled environment, usually by comparing it to a placebo or standard treatment. On the other hand, RWE studies typically aim to understand how an intervention works in routine clinical practice, often focusing on outcomes such as long-term effectiveness, side-effects, quality of life, and cost-effectiveness.
 
[2] Study Design and Methodology: Clinical trials, especially phase III, are predominantly randomized controlled trials (RCTs) where subjects are randomly assigned to the intervention or control group to minimize bias. They follow a pre-specified protocol and are conducted under tightly controlled conditions. RWE studies, on the other hand, are typically observational in nature and analyze data from sources like electronic health records (EHRs), claims databases, or patient registries.
 
[3] Setting: Clinical trials are conducted in specific, controlled environments and follow a strict protocol. RWE studies are conducted in routine clinical practice settings, making them more representative of ‘real-world’ conditions.
 
[4] Population: Clinical trials often have strict inclusion and exclusion criteria, resulting in a relatively homogeneous group of participants. This can limit the generalizability of the results. RWE studies, in contrast, involve broader, more diverse populations (including those often excluded from trials like the elderly, people with multiple co-morbidities, etc.), making the findings more generalizable to everyday practice.
 
[5] Data Collection: In clinical trials, data collection is rigorous, detailed, and specific to the trial endpoints. Adverse events are actively sought and documented. RWE studies primarily rely on existing data sources such as EHRs, patient registries, or insurance claims data. This can potentially lead to incomplete or inaccurate data.
 
[6] Intervention: In clinical trials, the intervention (dosage, frequency, duration, etc.) is pre-specified and strictly monitored. In RWE studies, interventions reflect routine clinical practice and may vary widely.
 
[7] Follow-up: Clinical trials have a defined follow-up period while RWE studies can often provide information on long-term outcomes, given they use data from routine clinical practice over longer periods.
 
While clinical trials provide the highest level of evidence for determining a treatment’s efficacy, RWE studies complement this by providing evidence on real-world effectiveness and long-term safety.

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Real World Evidence (RWE) 101 – Protocol Considerations2023-08-07T16:38:31+00:00

Real World Evidence (RWE) 101 – PASS Approval Requirements

RWE 101 – PASS Approval Requirements

 

Post-authorisation safety studies (PASS) are studies conducted after a medicine has been authorized (licensed) with the goal of acquiring more data about the medicine’s safety, or to measure the effectiveness of risk-management measures. These studies play a vital role in understanding the safety and effectiveness of a drug in a real-world context.
 
While specific requirements can vary by country, they often include:
 
[1] Ethics Committee Approval: Any study involving human subjects generally needs to be approved by an Ethics Committee (EC) or Institutional Review Board (IRB). This body ensures that the study is designed and implemented in a manner that respects the rights, safety, and well-being of the participants (i.e., compliance with the Declaration of Helsinki).
 
[2] Regulatory Approval: Depending on the country and type of PASS (e.g., Category 1, 2, 3, or voluntary PASS) additional regulatory approval may be needed. For instance, in the European Union, any category 1 or 2 PASS protocol of a medicine authorised through the Centralised Procedure has to be approved by the European Medicines Agency (EMA).
 
[3] Data Protection Laws Compliance: Studies must comply with all relevant data protection laws (e.g., GDPR). This includes regulations on the use and sharing of personal data, as well as provisions for protecting the privacy of participants.
 
[4] Study Registration: Most categories of PASS must be registered in a public database (i.e., EU PAS Register). This increases transparency and allows for the tracking and sharing of results.
 
[5] Adherence to Good Pharmacovigilance Practices (GVP): This is especially pertinent in the EU, where PASS must adhere to Module VIII of the GVP.
 
[6] Provision of Adequate Information to Participants: There’s usually a requirement that all participants must be given adequate information about the study, and that informed consent must be obtained.
 
[7] Reporting Requirements: There will be requirements to report adverse events, progress, and the final results to the respective regulatory bodies (i.e., ethics committees and national competent authorities).
 
However, these requirements can be subject to change over time and may vary in specifics from one country to another. Therefore, it’s crucial to consult with the appropriate regulatory body or a regulatory affairs professional familiar with these regulations when planning a post-authorisation safety study.

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Real World Evidence (RWE) 101 – PASS Approval Requirements2023-08-07T16:30:41+00:00

Real World Evidence (RWE) 101 – Categories of PASS

RWE 101 – Categories of PASS

Real-world evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a product derived from the analysis of real-world data (RWD). RWD and RWE are playing an increasingly important role in healthcare decisions.
 
In the context of pharmacovigilance, post-authorization safety studies (PASS) are studies performed after a medicine has been approved and is available on the market. The purpose of these studies is to obtain further information on a medicine’s safety, or to measure the effectiveness of risk-management measures.
 
Post-authorization safety studies (PASS) can be interventional (clinical trials) or non-interventional. As per EMA’s GVP Module V, there are 3 categories of PASS:
 
Category 1 PASS (Imposed PASS) – These are studies required by a regulatory authority as a condition of a (normal) marketing authorization. These studies are often required to clarify the safety profile of the drug, or to assess risks that were identified in pre-approval stages, but could not be fully characterized due to limitations like sample size of clinical trials or underrepresentation of certain populations. These studies are listed in Section II.C of the risk management plan (RMP) Summary.
 
Category 2 PASS (Specific Obligations) – These are studies that are specific obligations imposed when a medicine has received a conditional marketing authorisation. This applies to medicines that target conditions with an unmet medical need – for which no treatment option exists, or where they can offer a major therapeutic advantage over existing treatments. These studies are often required because the medicines approval has been accelerated to ensure timely access by patients, limiting the amount of safety data available at the time of approval. These studies are listed as “Specific Obligations” in Section II.C of the EPAR RMP Summary
 
Category 3 PASS (Other PASS) – These are studies might be required (as opposed to being imposed) by the EMA or a national competent authority in the RMP to investigate a safety concern or to evaluate the effectiveness of risk minimisation activities.  These studies are listed as “Other Studies” in Section II.C of the RMP Summary.
 
Category 1 and 2 PASS are supervised under Articles 107m, 107n-q of Directive 2001/83/EC, meaning the protocol and study report must comply with Annex III of Regulation 520/2012/EU and EMA’s GVP Module VIII. The protocol must be approved (endorsed) by the EMA’s Pharmacovigilance Risk Assessment Committee (PRAC) (medicines approved through the Centralised Procedure).
 
Category 3 PASS are supervised under Article 107m of Directive 2001/83/EC, which requires, for example, that studies are not promotional, healthcare professional renumeration is equivalent to fair market value, and final study reports should be send to the national competent authorities where the study is conducted.

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Real World Evidence (RWE) 101 – Categories of PASS2023-08-07T16:14:33+00:00

Real World Evidence (RWE) 101 – Safety Monitoring

RWE 101 – Safety Monitoring

Real World Evidence (RWE) complements clinical trials and provides additional insights that are difficult to achieve in controlled environments. Here’s why:

[1] Sample Size and Diversity: Clinical trials often involve a relatively small and selected population, while RWE studies involve larger and more diverse populations. This allows for a better understanding of the safety profile of a drug among different demographics, including age, race, gender, and individuals with different comorbidities.

[2] Long-term Follow-up: Clinical trials usually have a limited duration, while RWE can provide long-term safety data, including rare side effects that may only become apparent over time.

[3] Real-World Setting: Clinical trials are conducted in controlled settings and follow strict protocols. The patients who participate are often healthier and more adherent to treatment than average. On the other hand, RWE reflects the real-world setting, capturing the effects of the drug when used in routine clinical practice, which can differ substantially from trial conditions.

[4] Poly Pharmacology (Concomitant Medications): In the real world, patients often receive combinations of treatments, and the effectiveness and safety of these combinations can be different than individual treatments. RWE provides information about these combinations, something that is difficult to study in clinical trials.

[5] Post-Marketing Surveillance: Once a drug is approved and in use, RWE provides a mechanism to monitor its safety in the larger population. Post-marketing surveillance can help to identify rare adverse events that were not detected in clinical trials due to smaller sample size.

However, it’s important to note that RWE and clinical trials each have their strengths and weaknesses. Clinical trials remain the gold standard for demonstrating efficacy and obtaining regulatory approval because they can establish causality via randomization. RWE, while providing valuable insights on effectiveness and safety, often comes from observational studies, where it can be harder to determine cause-and-effect relationships because of potential confounding factors. Therefore, both are needed and (traditionally) used at different stages of the drug development and monitoring process.

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Real World Evidence (RWE) 101 – Safety Monitoring2023-08-07T16:06:48+00:00

Real World Evidence (RWE) 101 – How RWE is Being Used to Support the Treatment of Cancer

RWE 101 – How RWE is Being Used to Support the Treatment of Cancer

Real-world evidence (RWE) enhances cancer treatment through providing more comprehensive and personalized patient data. Here are summarized examples:

[1] Targeted Therapies for Lung Cancer: RWE aids in identifying actionable mutations in non-small-cell lung carcinoma (NSCLC), facilitating targeted treatments.
[2] Immuno-Oncology Treatments: Through studying melanoma patient responses to immune checkpoint inhibitors, RWE informs long-term safety, efficacy (effectiveness), and optimal usage.
[3] Treatment Adherence and Persistence: RWE helps determine factors affecting adherence to oral chemotherapies, enabling effective patient management.
[4] Clinical Trial Design: Real-world data can ensure clinical trial populations better reflect the real-world population’s diversity, increasing the trials’ relevance.
[5] Post-Market Surveillance: RWE allows monitoring of approved cancer drugs’ safety and effectiveness, identifying previously unknown adverse effects and comparing different treatments.
[6] Comparative Effectiveness Research: RWE can evaluate the benefits and harms of different treatments, such as drug classes or treatment methods, enhancing decision-making.
[7] Pediatric Oncology: RWE offers valuable insights into pediatric cancer treatment patterns and outcomes, critical given the ethical concerns with trials in pediatric populations.
[8] Health Economics and Outcomes Research: RWE assesses the cost-effectiveness of cancer treatments, informing coverage and reimbursement decisions.
[9] Precision Medicine: Real-world genomic data, combined with clinical outcomes, helps create more personalized treatment strategies, like using PARP inhibitors for BRCA-mutated ovarian cancer.
[10] Population Health Management: RWE can expose disparities in cancer care, prompting efforts to address these gaps.

In summary, RWE significantly contributes to cancer treatment. It complements clinical trials, supports personalized care, highlights patient voice, and improves overall cancer care quality. Despite data standardization and quality challenges, RWE’s potential to enhance cancer treatment remains vast.

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Real World Evidence (RWE) 101 – How RWE is Being Used to Support the Treatment of Cancer2023-08-07T15:57:12+00:00

Real World Evidence (RWE) 101 – Parkinson’s Disease

RWE 101 – Parkinson’s Disease

Real-world evidence (RWE) refers to clinical evidence regarding the usage and potential benefits or risks of a treatment derived from analysis of real-world data (RWD). RWD can include data from electronic health records (EHRs), claims and billing activities, product and disease registries, patient-generated data, and data gathered from other sources that reflect routine clinical practice.

In the context of Parkinson’s disease (PD), RWE can provide valuable insights into disease prevalence, real-world effectiveness of treatments, adherence to medication, quality of life, and more.

PD affects nearly 1% of individuals aged 60 and over. Real-world data, like those derived from large epidemiological studies or health databases, can help to reveal the true prevalence and incidence of PD in different populations. This information can assist in understanding the disease burden, aid healthcare planning, and inform research directions.

Treatment options for PD, as per conventional evidence, primarily consist of levodopa, dopamine agonists, and MAO-B inhibitors, along with non-pharmacological interventions like physical and occupational therapy, and in some cases, deep brain stimulation.

However, RWE provides additional context to these treatments. For example, RWE studies can demonstrate how these treatments are used in routine clinical practice, outside the controlled environment of clinical trials. They can highlight issues such as medication adherence, side-effects in real-world populations, long-term effectiveness, and the use of combination therapies.

RWE can also be used to understand disparities in treatment access and outcomes in different population subgroups. For instance, it might show that certain racial or socioeconomic groups have poorer access to PD treatments or worse outcomes, indicating the need for targeted interventions.

Moreover, RWE is crucial in identifying unmet needs and directing research towards novel treatments. For example, real-world data might reveal a significant number of PD patients not responding adequately to existing treatments, leading to the exploration of new therapeutic approaches like stem cell or gene therapy.

However, RWE has limitations, such as potential biases related to data collection and confounding factors, which should be taken into account when interpreting results.

In conclusion, RWE has a valuable role in understanding the real-world implications of PD, enhancing our knowledge about the disease, its treatment, and ultimately, improving patient care.

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Real World Evidence (RWE) 101 – Parkinson’s Disease2023-08-07T14:39:03+00:00

Real World Evidence (RWE) 101 – Benefits of RWE in the Context of Rare Diseases

RWE 101 – Benefits of RWE in the Context of Rare Diseases

 

Real-world evidence (RWE) refers to information on health care that comes from real-world settings, such as electronic health records (EHRs), insurance claims, product and disease registries, patient-generated data, and emerging sources like wearables and social media.

RWE is becoming increasingly important in the management of rare diseases like Addison’s disease, which is characterized by insufficient hormone production from the adrenal glands. Here are some benefits RWE can provide:

[1] Improved Understanding of Natural Disease Progression: Due to the low prevalence of rare diseases, our understanding of them often lacks detail. Real-world data can help fill these knowledge gaps by offering insights into the disease’s natural history and progression.

[2] Efficacy and Safety of Treatments: Clinical trials are the gold standard for assessing the efficacy and safety of new treatments, but they may not represent the broader patient population due to their strict inclusion and exclusion criteria. RWE, being derived from a diverse population, can provide insight into how a treatment works in a broader range of patients.

[3] Patient-focused Drug Development: With RWE, researchers can understand the burden of disease and the benefits patients value most, which can guide patient-focused drug development.

[4] Health Economics and Outcomes Research (HEOR): RWE can provide critical data for health economic evaluations, cost-effectiveness studies, and budget impact analyses.

[5] Early Identification and Diagnosis: Since many rare diseases often go undiagnosed due to their rarity and a lack of awareness among healthcare providers, RWE can help in early identification and diagnosis by revealing patterns or correlations that might not be apparent in smaller datasets.

[6] Post-marketing Surveillance: After a drug has been approved, RWE can be used to monitor its long-term effectiveness and side effects in a larger population.

[7] Guiding Clinical Practice: By understanding how treatments work in the real world, doctors can be better informed about the likely benefits and risks for individual patients, thus guiding personalized treatment.

However, it’s important to note that while RWE provides numerous benefits, it also comes with challenges, including data quality and integrity, privacy and security concerns, and the need for sophisticated analytical methods to derive meaningful conclusions from complex and heterogenous datasets.

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Real World Evidence (RWE) 101 – Benefits of RWE in the Context of Rare Diseases2023-08-07T14:32:56+00:00

Real World Evidence (RWE) 101 – Disease Prevalence vs Incidence

RWE 101 – Disease Prevalence vs Incidence

Real-world evidence (RWE), derived from real-world data (RWD), allows us to gain insights into disease prevalence and incidence outside of controlled clinical trial settings. This information plays a crucial role in shaping healthcare policies, identifying healthcare needs, directing research efforts, and improving patient care.

Disease prevalence refers to the total number of individuals in a population who have a specific disease at a given time. This includes both new (incidence) and pre-existing cases. RWE can offer a more comprehensive picture of disease prevalence by incorporating data from various sources such as electronic health records (EHRs), insurance claims data, patient registries, and more. This data is especially valuable in understanding chronic diseases, such as diabetes or heart disease, where prevalence data can reveal the burden of disease in a population, help to identify risk factors, and guide resource allocation.

Disease incidence, on the other hand, refers to the number of new cases of a disease that develop in a specific time period. Incidence data is particularly valuable in understanding infectious diseases or diseases linked to specific exposure or risk factors, like cancer or HIV/AIDS. Incidence data derived from RWD can help track disease outbreaks, identify populations at risk, and assess the effectiveness of preventative measures.

For example, using EHRs and public health databases, RWE can offer insights into the incidence of a new disease like COVID-19, track its spread, and monitor the effectiveness of public health measures in real-time.
RWE also plays a critical role in post-market surveillance of drugs and medical devices. By monitoring incidence rates of adverse events in the general population, it is possible to detect safety issues that may not have appeared during clinical trials, due to their limited size or exclusion of certain patient groups.

However, there are potential limitations to RWE including data quality, missing data, and bias in data collection. These factors should be considered while interpreting RWE for disease prevalence and incidence.

In conclusion, RWE provides a comprehensive and real-time view of disease prevalence and incidence in real-world settings, thereby informing health policy decisions, guiding research, and improving overall patient care.

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Real World Evidence (RWE) 101 – Disease Prevalence vs Incidence2023-08-07T14:27:06+00:00

Real World Evidence (RWE) 101 – Principles for Ensuring that Research Results are Reliable, Valid, and Objective

RWE 101 – Principles for Ensuring that Research Results are Reliable, Valid, and Objective

Ensuring that research results are reliable, valid, and objective requires careful planning, execution, and evaluation. Here are several key factors to consider:

1. Research Design: The study design should be robust and suitable for answering the research questions. It should incorporate procedures for controlling variables, randomizing assignments (if applicable), and testing hypotheses. The design should also minimize the potential for bias.

2. Sampling: The selection of participants or samples should be appropriate and unbiased. Larger sample sizes generally increase reliability and can improve validity. The sample should be representative of the population to which you want to generalize your findings.

3. Data Collection: The methods for collecting data should be consistent and standardized. Any measurement tools used should be reliable (provide consistent results over time) and valid (accurately measure what they’re supposed to measure).

4. Data Analysis: Statistical analysis should be appropriate for the type of data collected and the research questions. This includes correctly handling missing data and making proper inferences. Be cautious of multiple testing issues that can lead to false positives.

5. Replication: A study’s results are more reliable if they can be replicated by other researchers. To facilitate replication, provide a clear and thorough description of your methods (e.g., use the STaRT-RWE structured template for planning and reporting of real world evidence studies).

6. Peer Review: Have your research reviewed by others in your field before publishing. They can provide valuable feedback and catch any errors or inconsistencies you may have missed.

7. Transparency and Openness: Be open and honest about your methodology, data, results, and any potential conflicts of interest. This can include sharing your raw data and analysis scripts if possible.

8. Addressing Confounding Factors: Identify and control for potential confounding factors – variables that could cause both the independent and dependent variables to change, thereby creating a false impression of a cause-effect relationship.

9. Interpretation: Be careful not to overstate your findings. Make sure your conclusions are supported by your data, and acknowledge any limitations of your study.

10. Ethical Considerations: Ensure that your study complies with ethical guidelines. This includes respecting participants’ rights and privacy, obtaining informed consent, and avoiding harm.

By adhering to these principles, researchers can increase the chances that their findings will be reliable, valid, and objective. However, it’s also important to recognize that no study is perfect, and all research comes with some degree of uncertainty. The goal is to minimize this uncertainty as much as possible.

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Real World Evidence (RWE) 101 – Principles for Ensuring that Research Results are Reliable, Valid, and Objective2023-08-07T14:20:58+00:00
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