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1. An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, Pubrica
Group: www.pubrica.com
Email: sales@pubrica.com

2. In research, systematic reviews are like guiding stars, leading us to
evidence-based conclusions. Working with an abundance of data can be
challenging, but CHARMS (Checklist for critical Appraisal and data
extraction for systematic Reviews of prediction Modelling Studies) and
PROBAST (Prediction model Risk of Bias Assessment Tool) can help.
Data extraction is like gathering supplies for a journey, while bias
assessment is like charting a safe course. CHARMS helps gather data
efficiently, like a well-prepared sailor stocking up on provisions.
Meanwhile, PROBAST acts as a lookout, helping spot and avoid biases
that could throw us off course. These frameworks simplify our tasks,
making research smoother.

3. In the systematic review process, data extraction means collecting important information
from different studies and organizing it neatly. This can take a lot of time, and mistakes
can happen, especially when there are many studies to go through. Researchers often
need help gathering data in the same way across different reviewers and making sure it’s
accurate and complete.
DATA EXTRACTION AND BIAS ASSESSMENT IN RESEARCH: THE ROLE OF
TOOLS LIKE CHARMS AND PROBAST
Bias assessment is about checking if there are any factors in the studies that could
make the results less reliable. This step is important to determine whether the evidence
is trustworthy. It takes work because it involves understanding research methods and
statistics.
To make these tasks easier, researchers have created tools like CHARMS and PROBAST.
CHARMS helps collect data from prediction modeling studies in a standard way, and
PROBAST helps check if prediction models have biases. These tools provide clear steps to
follow, which saves time and ensures the review is done well. They help researchers be
consistent and reduce mistakes.

4. CHARMS provides a structured approach to data extraction, ensuring that all
relevant information is captured consistently. It helps researchers collect data
from prediction modeling studies in a constructed way. It has a checklist that
guides reviewers on what information to gather. This checklist ensures that
everything important is noticed, making the results more trustworthy.
HOW CHARMS SIMPLIFIES THE PROCESS
AND IMPROVES CONSISTENCY
One great thing about CHARMS is that it makes sure all reviewers follow the
same standards. This reduces differences between reviewers, which is important
in systematic reviews where many people are involved.
CHARMS is also flexible and can be used for different types of studies. It’s not
limited to one field, so it’s useful for various research questions.
CHARMS helps with data extraction and estimates bias in studies. It includes a
feature to detect bias, which enhances transparency and accountability in the
review process.

5. HOW PROBAST STREAMLINES BIAS
ASSESSMENT AND ENHANCES VALIDITY.
PROBAST helps researchers check for bias in prediction model studies. It
looks at four areas: who was chosen for the study, the factors being
predicted, the outcomes measured, and how the analysis was done. By
systematically examining these areas, researchers can spot biases that
affect the prediction model’s credibility.
One great thing about PROBAST is that it guides researchers through
the evaluation process. It provides clear questions for each area,
making sure everything important is noticed.
Using PROBAST helps researchers check for bias thoroughly, making
their reviews more reliable. It makes sure biases aren’t overlooked,
which makes the findings more reliable for making decisions based on
evidence.

6. STEP-BY-STEP GUIDE ON IMPLEMENTING CHARMS AND PROBAST IN
SYSTEMATIC REVIEWS
1.Get to Know CHARMS: CHARMS is a helpful tool for critical appraisal and data extraction in prediction modeling studies. It
comprises a checklist for systematic reviews that ensures the accurate collection of essential information.
2.Learn about PROBAST: PROBAST evaluates prediction model study bias using signaling questions. Familiarize yourself with its
domains to assess study quality effectively.
3.Customize CHARMS and PROBAST: Adapt these tools to match your review’s objectives and questions. Make sure to cover all
relevant aspects and biases specific to your study.
4.Create a Data Extraction Form: Develop a structured form based on CHARMS elements to extract data consistently from all
included studies. Include study details, bias domains, and other relevant info.
5.Train Your Reviewers: Training on CHARMS and PROBAST is necessary for consistent and accurate reviews.
6.Use CHARMS for Extraction: Gather data from each study using your customized data extraction form. This method
guarantees the capture of all the essential information.
7.Employ PROBAST for Bias Assessment: Use PROBAST to assess bias in prediction models. Evaluate each domain and potential
biases with it signaling questions.
8.Document Your Findings: Record your data extraction and bias assessment findings using CHARMS and PROBAST. This
documentation will be essential for your review process and any future updates.

7. In conclusion, integrating CHARMS and PROBAST into systematic reviews offers a powerful solution for researchers
seeking efficiency and accuracy. CHARMS ensures consistent data extraction, while PROBAST facilitates thorough
bias assessment, streamlining the review process. By simplifying these critical tasks, researchers can enhance the
reliability and transparency of their findings, ultimately advancing evidence-based decision-making in various fields.
With their structured approaches and comprehensive frameworks, CHARMS and PROBAST stand as invaluable tools
in the pursuit of robust systematic reviews.
Get reliable systematic review services from Pubrica! Our experts will gather and analyze research thoroughly, giving
you insightful reviews you can trust. Let’s simplify your review process – reach out to us today!

8. REFERENCE
1.Fernandez-Felix, B. M., López-Alcalde, J., Roqué, M., Muriel, A., & Zamora, J. (2023). CHARMS and
PROBAST at your fingertips: a template for data extraction and risk of bias assessment in
systematic reviews of predictive models. BMC Medical Research Methodology, 23(1), 1-8.
2.Kuo, R. Y., Harrison, C., Curran, T. A., Jones, B., Freethy, A., Cussons, D., … & Furniss, D. (2022).
Artificial intelligence in fracture detection: a systematic review and meta-analysis. Radiology,
304(1), 50-62.
3.Kraft, S. A., McMullen, C., Lindberg, N. M., Bui, D., Shipman, K., Anderson, K., … & Lee, S. S. J. (2020).
Integrating stakeholder feedback in translational genomics research: an ethnographic analysis of
a study protocol’s evolution. Genetics in Medicine, 22(6), 1094-1101

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