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She joined the MJH Life Sciences team in December 2019. She graduated from Youngstown State University in 2019 with a bachelor's degree in journalism and a minor in political science. Prior to graduating, Morgan worked as the editor-in-chief of her college newspaper. She went on to work as an assignment editor at a broadcast news station in Youngstown, Ohio, before joining 

 You can reach her at mebert@mjhlifesciences.com.

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A recent clinical study presented by Koji Ishikawa, MD, PhD, orthopedic spine surgeon at Duke University, and Tony M. Keaveny, PhD, Founder and Chief Science Officer of O.N. Diagnostics, compared the effects of romosozumab, teriparatide, and denosumab on bone strength in patients with osteoporosis. 

The analysis focused on the hip and spine, where fracture risk is particularly great. Results showed that romosozumab provided substantially greater improvements in bone strength after 1 year of treatment compared to the other 2 drugs. At the spine, for example, romosozumab increased bone density by approximately 25% but boosted bone strength by about 40%, highlighting that strength gains are not fully reflected by bone density measurements from standard DXA scans.

The findings are significant because fracture prevention depends more on improved breaking strength than on density alone. Data from real-world clinical care also suggest even greater percentage gains than those seen in earlier phase-2 and phase-3 trials. 

Notably, romosozumab demonstrated the unique ability to transform highly osteoporotic vertebrae into bones at much lower risk of biomechanical failure, as shown through virtual stress testing models. According to the researchers, romosozumab stands out as the most effective treatment for strengthening both hip and spine bones, offering a compelling advantage over teriparatide and denosumab.

Please provide an overview of your presentation about bone strength from romosozumab vs teriparatide or denosumab.

This study compared the breaking strength of the hip and spine bones for different osteoporosis drug treatments and showed that the strength benefits after 1 year of treatment were substantially greater for romosozumab compared to both teriparatide and denosumab.

Spinal instrumentation remains challenging in patients with bone fragility. The concept behind this project is to provide additional support for achieving favorable surgical outcomes, beyond surgical techniques. Based on simulation-based biomechanical analysis, we found that romosozumab offered multiple advantages over denosumab and teriparatide in terms of biomechanical parameters relevant to spinal surgery.

What is the significance of these findings?

Changes in bone density as measured by clinical-standard DXA testing are difficult to interpret because what matters most in terms of fracture reduction is how much the 

 changes. This study is significant because it demonstrates the substantial benefits for breaking strength – more than for bone density. For example, at the spine, romosozumab increased bone density by about 25% but bone strength by about 40%. So, the benefits of the treatment are underestimated when measured by bone density. And of course, those benefits were greater for romosozumab than either of the other 2 treatments.

Evaluating mechanical parameters such as screw fixation strength or bone-breaking force in clinical practice for assessing drugs effects is impractical and often difficult with traditional biomechanical methods. To address this, we developed a simulation approach using patient CT data. Our findings provide a new perspective on their effectiveness in the context of implant surgery.

What were the main takeaways of your presentation?

As we have seen in other clinical trials, romosozumab is the better treatment in terms of its bone-strengthening benefits, both at the hip and spine. Here we have data from actual clinical care.

After 1 year of treatment, romosozumab showed greater improvements than denosumab and teriparatide in surgical instrumentation-related biomechanical analyses.

What other research about the impact of romosozumab on bone strength would you like to highlight?

These results suggest even greater gains, percentage-wise at least, for these highly osteoporotic and treatment-naïve patients from clinical care than what we observed in a prior phase-2 BCT study in women with low bone mass (Keaveny JBMR 2017) and also in a phase-3 imaging substudy of osteoporotic women with prior bisphosphonate therapy (Langdahl Lancet 2017).

In a previous study, we were the first to demonstrate the potential benefits of short-term romosozumab treatment (3 months) in reducing postoperative complications after spinal surgery (Ishikawa K, JOR Spine 2024). Taken together with the present findings, our research further supports the role of romosozumab for surgical support.

These results are particularly compelling at the spine for romosozumab because the drug benefit is so large — it takes a highly osteoporotic bone and transforms it into one at much lower risk of biomechanical failure. This is seen visually with the virtual stress testing. Here, virtual forces are placed on the bone that would normally fracture and crush an osteoporotic bone. After treatment with romosozumab, that same level of force produces almost no damage in the bone. Romosozumab appears to be the only drug treatment that can transform the osteoporotic vertebra in this way.

Even the best surgeons face complications when patients have osteoporosis. Yet perioperative bone health care is often overlooked. Our studies underscore the importance of assessing and managing bone health in perioperative settings to improve surgical outcomes.

A recent study found that romosozumab significantly outperformed teriparatide and denosumab in improving hip and spine bone strength.

Clinical

Romosozumab outperforms teriparatide and denosumab in bone strength

 levels are reduced by continuous glucose monitoring (CGM) vs self-monitoring of blood glucose, alongside a potential reduction in large for gestational age (LGA) risk, according to a recent study published in the 

American Journal of Obstetrics & Gynecology.

More than 17% of live births annually are impacted by diabetes in pregnancy (DIP), with increased risks of stillbirth, congenital malformations, LGA, and other complications. Glucose management is often accomplished through self-monitoring of blood glucose (SMBG), but data have indicated improved outcomes when adding CGM.

“Despite increasing interest in the use of CGM in [type 2 diabetes (T2D)] and [gestational diabetes mellitus (GDM)], it is uncertain whether similar benefits in pregnancy outcomes are seen,” wrote investigators.

A systematic review and meta-analysis were conducted to compare the outcomes of CGM vs SMBG for managing DIP. Articles published from January 2003 to August 2024 were obtained through systematic searches of the Embase, Medline, CINAHL, CENTRAL, and Scopus databases.

Studies with participants using CGM for type 1 diabetes (T1D), T2D, or GDM with an SMBG comparator group were included in the analysis. Reporting maternal glycemia or perinatal outcomes was also required for inclusion. Exclusion criteria included nonpregnant patients, the absence of a comparator SMBG group, and the study conducted in an inpatient setting.

Two independent study authors extracted study and participant characteristics, consulting a third author to resolve discrepancies. Cohort characteristics, participant characteristics, CGM data, and outcomes were extracted for assessment, along with links between CGM metrics and perinatal outcomes.

There were 18 studies included in the final analysis, 14 of which were randomized controlled trials (RCTs) and 4 were quasi-experimental. Three CGM methods were reported across these studies, including real-time CGM in 6, intermittently scanned CGM in 5, and retrospective CGM in 6. A mix of real-time CGM and intermittently scanned CGM was used in 1 study.

was reported for DIP following CGM vs SMBG in a meta-analysis of 7 RCTs, with a mean difference (MD) of -0.22%. An improvement from CGM was also reported in quasi-experimental data, but the evidence had low certainty.

Another RCT highlighted reduced third-trimester HbA

 from CGM vs SMBG in patients with T1D, with an MD of -0.18% Quasi-experimental data indicated an MD of -0.30%, supporting this association. However, no differences between CGM and SMBG were reported across 2 studies assessing third-trimester HbA

For mixed DIP, the MD in third-trimester HbA

 for CGM vs SMBG across 4 RCTs was -0.60%, highlighting a reduction. A decline in third-trimester HbA

 was also reported for GDM across 7 RCTs, with an MD of -0.18%.

Associations were reported for CGM glucose metrics and LGA. Specifically, reduced LGA was reported in patients with first-trimester CGM use and lower mean sensor glucose (SG), with an OR of 1.04. A single trial showed benefits toward LGA when using CGM for pregnancy duration, reporting an OR of 0.54.

A decline in neonatal hypoglycemia based on an OR of 0.56 was also reported for CGM vs SMBG across 2 RCTs. Small for gestational age odds were not influenced by the glucose monitoring method used. Overall, the results highlighted reduced third-trimester HbA

 and mean SG from CGM use in T1D and GDM, leading to a decrease in LGA.

“Ongoing studies including RCTs of CGM use in T2D and GDM…as well as observational studies…alongside health economic analyses, will provide important insights into the role of CGM use in the management of both T2D and GDM, and in the prediction of GDM and perinatal complications more broadly,” wrote investigators.

Burk J, Ross GP, Hernandez TL, Colagiuri S, Sweeting A. Evidence for improved glucose metrics and perinatal outcomes with continuous glucose monitoring compared to self-monitoring in diabetes during pregnancy. 

2025;233(3):162-175. doi:10.1016/j.ajog.2025.04.010

. Continuous glucose monitoring in pregnant women with type 1 diabetes (CONCEPTT): a multicentre international randomised controlled trial. 

. 2017;390(10110):2347-2359. doi:10.1016/S0140-6736(17)32400-5

A study found continuous glucose monitoring improves glycemic control vs self-monitoring in diabetes during pregnancy.

Continuous glucose monitoring lowers HbA1c and LGA risk in pregnancy

Ovarian cancer

Jesus Gonzalez Bosquet, MD, PhD, associate professor of obstetrics and gynecology at The University of Iowa, highlighted the efficacy of a machine learning model using blood-based biomarkers to identify ovarian cancer.

Ovarian cancer remains one of the most difficult gynecologic cancers to detect early, and this significantly impacts patient survival outcomes. According to Gonzalez Bosquet, the primary challenge is the lack of effective early screening or detection methods. Current tools, such as ultrasound and tumor markers, have been tested in multiple studies in the United States and abroad, but none have demonstrated consistent accuracy. 

As a result, most patients are diagnosed at advanced stages, when treatment options are limited and survival rates drop significantly. Gonzalez Bosquet noted that 5-year survival rates for early-stage ovarian cancer reach approximately 95%, but this falls between 40% and 50% for patients diagnosed at later stages, underscoring the need for earlier detection strategies.

To address this gap, Gonzalez Bosquet and his team have explored the use of machine learning models to identify ovarian cancer through blood-based biomarkers. Their work focuses on detecting methylated DNA fragments shed by tumors into the bloodstream. Starting with a platform that examined more than 850,000 methylation probes, the researchers used machine learning to narrow the list down to 9 probes that showed strong potential for accurately identifying ovarian cancer. While promising, these findings are still in the pilot phase and require further validation before they can be used in clinical settings.

According to Gonzalez Bosquet, the next step in this research is to confirm whether these methylated probes can be reliably detected in blood samples, not just in surgical tissue specimens. He that his team, in collaboration with Mayo Clinic, has submitted a project aimed at this validation step. If successful, the model will need to be tested in large-scale screening studies involving both patients with and without ovarian cancer to determine its true diagnostic accuracy and clinical value.

Looking ahead, Gonzalez Bosquet envisions practical applications of these artificial intelligence (AI) models that would make them accessible to clinicians worldwide. Once fully developed, the models could be hosted on web-based platforms, allowing physicians to upload data such as imaging scans or blood test results. The system would then provide a risk assessment, ranging from low to high probability of ovarian cancer. This streamlined, user-friendly approach could integrate seamlessly into clinical workflows, offering physicians a powerful tool for earlier and more accurate cancer detection.

Ultimately, Gonzalez Bosquet emphasized that while the technology is still under development, AI-driven models hold great promise in transforming ovarian cancer diagnosis, potentially improving survival rates by identifying the disease before it reaches advanced stages.

Gonzalez Bosquet J, Wagner VM, Russo D, et al. Identifying ovarian cancer with machine learning DNA methylation pattern analysis. 

2025;15(1):20910. doi:10.1038/s41598-025-05460-9

Jesus Gonzalez Bosquet, MD, PhD, discusses how machine learning could improve early ovarian cancer diagnosis by identifying methylated DNA in blood.

Jesus Gonzalez Bosquet, MD, PhD, highlights test for earlier ovarian cancer detection

As Menopause Awareness Month approaches in October, new polling data highlight widespread uncertainty among women about the role of diet in alleviating menopause symptoms. A survey conducted by the Physicians Committee for Responsible Medicine (PCRM) and Morning Consult found that fewer than half of women recognized diet as a factor influencing the number and severity of hot flashes.

The survey, conducted on August 6 and 7, 2025, included 1155 women across the United States. Results showed that only 43% of respondents believed diet influences hot flashes, despite research suggesting otherwise.

The poll also assessed perceptions of soy- and plant-based foods. Nineteen percent of women thought soy products should be avoided during menopause, while 21% thought soy need not be avoided. Responses regarding ultraprocessed plant-based foods, such as plant-based meats or dairy alternatives, were mixed. Eleven percent believed these foods reduce hot flashes, while 22% thought they increase them. When asked about weight gain, 13% believed such foods lead to weight loss, compared with 26% who associated them with weight gain.

The survey findings contrast with published research. Hana Kahleova, MD, PhD, director of clinical research at the PCRM, stated, “Our research has found that a low-fat plant-based diet that includes soybeans can significantly reduce hot flashes and weight in postmenopausal women. Women can even experience these health benefits when their diet includes plant-based foods that are considered ultraprocessed—like soy milk and plant-based meat alternatives.”

Kahleova, along with Neal Barnard, MD, president of the PCRM, led the Women’s Study for the Alleviation of Vasomotor Symptoms (WAVS) trial, published in 

 in 2023. That study found that a plant-based diet incorporating soy reduced moderate to severe hot flashes by 88% and supported an average weight loss of 8 pounds over 12 weeks. Secondary analysis suggested that the benefit occurred regardless of whether the plant-based foods were unprocessed or ultraprocessed.

The WAVS trial enrolled 84 postmenopausal women who reported at least 2 hot flashes daily. Participants were randomly assigned to follow a low-fat, vegan diet that included half a cup of cooked soybeans daily, or to continue their usual diet. After 12 weeks, the intervention group reported substantial reductions in symptoms compared with controls.

Approximately three-quarters of women experience hot flashes during menopause, but these symptoms often receive limited attention in routine care. A 2024 study published by the Menopause Society reported that symptom management is frequently underemphasized in primary care settings.

Given the gap between public perception and clinical evidence, PCRM physicians urge clinicians to discuss diet as part of menopause management. “This Menopause Awareness Month—and all year long—I urge physicians and other clinicians to encourage their patients who are in any phase of menopause to try a plant-based diet to help fight hot flashes, reduce their weight if needed, and improve other health conditions,” said Vanita Rahman, MD, clinic director of the Barnard Medical Center in Washington, DC.

The authors of the WAVS trial emphasize that dietary interventions can provide nonpharmacologic options for symptom management, particularly for patients seeking alternatives or adjuncts to hormone therapy.

While research supports plant-based dietary strategies for reducing vasomotor symptoms and promoting weight loss during menopause, the new poll suggests that most women remain uncertain about the role of diet. Increasing awareness may allow physicians to provide evidence-based nutritional guidance to improve patient outcomes.

Physicians Committee for Responsible Medicine. New poll: most women don’t know that diet change can reduce hot flashes. News release. EurekAlert. September 8, 2025. Accessed September 8, 2025. https://www.eurekalert.org/news-releases/1097460

Physicians Committee for Responsible Medicine. Menopause Diet Poll. August 2025. Accessed September 8, 2025. https://pcrm.widen.net/s/rzdd9blfzj/menopause-diet-poll-physicians-committee-for-responsible-medicine-morning-consult

A national poll finds most women underestimate diet’s role in reducing menopause symptoms, despite evidence for plant-based diets with soy.

Many women unaware of dietary effects on menopause symptoms, poll shows

Saying "obstetrician-gynecologist" is a mouthful for most people, and it's probably the most abbreviated specialty in medicine, both spoken and written. However, there doesn't seem to be a consensus on how to pronounce OB-GYN. First, is it the two-syllable "O-B" or the monosyllabic "Ob"? Second, is it "gin" or "gyne" (like "Lyme")? I wonder if you have a preference. I know I do.

Almost nobody says "obstetrician-gynecologist" when speaking about these specialist physicians. But what's the "correct" way to pronounce OB/GYN?

June Keeling

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