As part of its mission to support the Turner Syndrome (TS) community, the Turner Syndrome Foundation (TSF) spreads awareness of earlier diagnosis. Early diagnosis means that TS patients and their caregivers can better prepare for any related medical issues and take advantage of available treatments.
The Importance of Early Diagnosis
Early diagnosis is crucial because it helps:
- give growth hormone and/or hormone replacement therapies enough time to improve the health and height of patients with TS; and
- make potentially lifesaving medical interventions for heart, kidney, and other health challenges possible, keeping them from developing into dangerous problems as time passes.
Despite the fact that scientists have known about TS for decades, patients still often receive late diagnoses or misdiagnoses. That is why it’s crucial for both doctors and patients to spread TS awareness.
This article discusses a recent research study about new technology that can potentially lead to earlier TS diagnoses. This technology is called Electronic Health Records (EHRs), which are algorithm-based alert systems. The study’s discoveries are causing doctors to consider using EHRs to diagnose TS earlier than ever before.
Note: Please see the Glossary below for an explanation of some of the terms in this article.
Purpose of the Study
Because late or missed TS diagnoses can negatively impact patients, Dr. Eirene Alexandrou and her fellow researchers studied the possibility of using EHRs to improve diagnoses in their article, “Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner Syndrome.”
Since previous studies showed that EHRs that automatically monitor growth patterns can enhance diagnoses of growth-related disorders, Alexandrou’s group predicted that these systems can help diagnose TS.
For the study, they used an algorithm that analyzed the standard deviation of absolute height and deviation from the patients’ mid-parental height (MPH) to determine whether they would aid in identifying TS patients and lead to earlier diagnoses.
Researchers from the Cincinnati Children’s Hospital Medical Center in Cincinnati, OH included:
- Eirene Alexandrou, MD
- Guillaume Labilloy, ME
- Leah Tyzinski, BA, CCRP
- Teresa A. Smolarek, PhD, who is also from the University of Cincinnati’s Pediatrics Department
- Yongbo Huang, MS
- Philippe Backeljauw, MD
Researchers from the Children’s National Health System’s Endocrinology Division in Washington, D.C. included:
- Melissa Andrew, BS
- Andrew Dauber, MD, also with the George Washington School of Medicine and Health Sciences’ Pediatrics Department in Washington, D.C.
Another researcher was Catalina Cabrera-Salcedo, MD, from the University of Louisville’s Endocrinology in Kentucky.
Scope of the Study
The researchers collected between 2012 and 2017 from children at the Cincinnati Children’s Hospital Medical Center’s Endocrinology Clinic. All of the children exhibited shorter stature than 95% of children with no disease, known as idiopathic short stature (ISS).
The Eunice Kennedy Shriver National Institute of Child Health and Human Development funded the study. The researchers submitted the article for publishing in June 2019.
How the Study Was Conducted
First, the Cincinnati Children’s Hospital Medical Center’s Institutional Review Board (IRB) approved the project. Then the group obtained consent for the patients to participate in the study. After that, the group set about determining whether an EHR program could identify any possibly missed cases of TS in patients with ISS. The researchers then began to collect and analyze the data by:
- collecting data for female patients with ISS from the hospital’s EHR system. They further analyzed the data with an algorithm they designed;
- pinpointing, with the algorithm, patients whose heights were more than two standard deviations below average, weights greater than the bottom 5% of the population, and who did not exhibit chronic illness;
- identifying patients who were one or more standard deviations below their MPH but had not received genetic testing;
- designing the algorithm to identify ISS patients with a distance to MPH greater than one standard deviation, indicating the possibility that they might have TS;
- using data from TS patients from the hospital’s EHR system in a control group so they knew how much of the participants’ data matched existing data;
- performing microarray analysis to identify copy number variation and structural variants, as well as the level of genetic mosaicism;
- performing statistical analysis to compare both the TS and ISS patient data;
- analyzing height standard deviation score (HSDS) and MPH data from 216 ISS patients’ and 76 TS patients’ samples as a control group.
- collecting 32 ISS samples for microarray analysis and five for the TS control group.
Results Using EHRs
The study confirmed that many female patients with ISS do not get genetically tested for TS. This goes against guidelines from a 2017 International consensus meeting on TS endorsed by the European Society for Endocrinology and the Pediatric Endocrine Society, which suggest testing for TS in all female patients with ISS. Using this algorithm, the researchers made interesting discoveries, such as:
- The algorithm was successfully able to identify all the TS patients, demonstrating its capabilities.
- 189 ISS patients fulfilled the EHR’s criteria, indicating that they might have TS. However, 38% of this group had never received any genetic testing.
- The other 62% of patients who had previously received genetic testing demonstrated greater distances to MPH, meaning the difference between their actual heights and their predicted heights was more severe.
- This may suggest that, according to the parameters designed by the researchers, all of the 189 ISS patients with a distance to MPH greater than one standard deviation likely should have been karyotyped. However, only the more noticeable cases were tested.
Results of Genetic Analysis
Microarray analysis helped the researchers make other interesting discoveries, including:
- They identified two undiagnosed TS cases and a patient with a previously undiagnosed copy number variant affecting height.
- Both TS cases exhibited mosaicism, demonstrating how it can sometimes lead to misdiagnosis, as distance to MPH is not always as extreme.
- Six percent of patients studied had undiagnosed TS caught by microarray analysis.
- All three of the above patients had seen physicians for height- and/or weight-related concerns, but they either received misdiagnoses of nutritional issues, did not receive follow-up care, or never had genetic testing.
While there is no other research cited by the authors about the effects of EHRs on TS diagnoses, there are sources confirming improvements in testing and the importance of MPH as an indicator of TS.
A systematic review conducted by a team led by the Cochrane Effective Practice and Organization of Care Group and Kaveh G Shojania, “The effects of on-screen, point of care computer reminders on processes and outcomes of care,” found that the median improvement in genetic tests ordered as a result of EHRs ranged from 4 to 10%.
While these improvements seem small, it supports the authors’ claims that EHRs used for TS can promote genetic testing and lead to more timely and accurate diagnoses.
Also, in a European Journal of Pediatrics study led by Yasmine Ouarzki, “Measured parental height in Turner Syndrome – a valuable but underused diagnostic tool,” the researchers’ findings confirm the use of MPH as a useful tool for detecting potential TS cases, reaffirming one of the main components of the algorithm.
Limitations of this study included:
- The researchers collected data from a large academic center with a specialized TS clinic that receives referrals for potential TS cases. Thus, the results and percentages gathered are potentially skewed and not likely applicable on a larger scale.
- Because the center has a TS clinic and receives referrals for potential cases, the researchers suggest that the number of undiagnosed cases could possibly be higher in the general population.
- The HSD cutoff used in their algorithm sets a limit of HSDS below -2. There are cases of TS above this cutoff, so this threshold still leaves room for some undiagnosed cases.
The above factors suggest that the algorithm needs more refinement to encompass all potential TS symptoms, while still remaining specific enough to make it practical.
The researchers disclosed the following conflicts of interest:
- Dr. Backeljauw received research support from pharmaceutical companies like Novo Nordisk, Ipsen, Opko, and Sandoz. They also received consulting fees from Novo Nordisk and Sandoz.
- Dr. Dauber also received consulting fees from Novo Nordisk, Sandoz, Pfizer, Ipsen, Ascendis, and OPKO Biologics.
Suggestions for Future Research
Because 38% of female patients with ISS did not receive genetic testing for TS and the algorithm’s success in identifying known and unknown TS cases, the researchers suggest the implementation of an alert feature in EHR programs for potential indicators of TS. This would help notify doctors when patients should receive genetic testing.
They also suggest more research into algorithm parameters that would not exclude individuals with an absolute HSDS above -2, to potentially identify more TS cases.
Importance for the TS Community
Advocating for TS awareness is important, as it equips both patients and doctors to recognize signs and receive earlier diagnoses. As previously discussed, early detection of TS allows for growth hormone treatments, therapies and potentially lifesaving medical interventions. Supporting the TS community and advocating for TS awareness increase opportunities and help individuals with TS overcome their various challenges.
If you would like to help promote TS awareness, you can:
- join TSF’s professional membership to learn how to help the TS community get the medical services they need and support them,
- join TSF’s educator membership and check out TSF’s resources to learn more about TS and the TS community and how to support students with TS, and
- participate in TS research or collaborate with TSF for your research project to help the TS community.
- Electronic Health Records (EHR’s): algorithm-based alert systems through Electronic Health Records
- Height standard deviation score (HSDS): compares a patient’s height to an average; a positive HSDS means that a patient is taller than average; a negative HSDS means that a patient is shorter than average
- Idiopathic short stature (ISS): a condition characterized by having a shorter height than 95% of people with no medical conditions, or having a HSDS lower than two standard deviations below average
- Microarray analysis: a technique used to analyze gene expression
- Mid-parental height (MPH): a child’s predicted height determined by the average of their parents’ heights or the the average height standard deviation scores of both parents
- IRB (Institutional Review Board): a group at an institution, such as a college or hospital, that reviews, revises, and approves research projects that involve human participants and ensures that patients’ rights are protected during the research project
- Copy Number Variation: occurs when there are different amounts of a certain gene
- Structural variants: alterations in a chromosome’s structure
- Mosaicism: occurs when different cells have different genetic variations; can sometimes delay a TS diagnosis, as warning signs like short stature may be less noticeable
- Standard deviation: measures the distribution of data, or how far data is from the average (mean); for example, being one standard deviation below the mean for height indicates that your height is lower than average, and being two standard deviations below the mean would mean your height is even lower than the average
Takeaway - What You Can Do Now
- Early detection of TS is important because it allows for timely implementation of hormone therapies and other necessary medical interventions .
- While it is well known that early diagnoses of TS are crucial, many late diagnoses still occur.
- Researchers recommend that all female patients with ISS be tested for TS, but that is often not the reality. The 38% of TS patients in this study who were not tested for TS is a striking example of this.
- The researchers’ algorithm provides an easily implementable and seemingly successful option to provide physicians with EHR alerts when a patient might need testing for TS. This could lead to more timely diagnoses.
- If you want to help increase early diagnoses of patients with TS, please support TSF by advocating and educating others on TS to support the TS community.
Written by Julianne Franca, a TSF volunteer blog writer. Edited by Prabhat Sharma, TSF volunteer blog editor, and Susan Herman, TSF volunteer lead blog editor.
© Turner Syndrome Foundation, 2021