Hello Health Rounds readers! Today we highlight two studies that could lead to improved healthcare for women: one that tested a drug that helped women with a deadly cancer survive significantly longer, and another that demonstrates the ability of artificial intelligence to detect a serious pregnancy complication.  

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Patients with one of the deadliest gynecological cancers had dramatically improved survival when an experimental drug was added to treatment with a standard chemotherapy medication in a mid-stage trial in Belarus, researchers say.

The 30 women in the study had ovarian cancer resistant to first-line “platinum-based” chemo drugs, along with elevated blood levels of a cancer protein called CA-125.

All received standard gemcitabine chemotherapy, and half also received elenagen, being developed by CureLab Oncology, as a once-weekly injection into the muscle.

Patients in the elenagen group lived significantly longer, with a median survival of more than 25 months, compared to roughly 13 months with gemcitabine alone.

“Several patients survived years beyond expected survival for this disease setting,” the researchers said in a statement.

Treatment with elenagen also reduced mortality risk by nearly 60%, the researchers found.

“What makes these results remarkable is not only the magnitude of the survival benefit, but that it was achieved without added toxicity and without a specific biomarker,” study leader Dr. Sergei Krasny of the N. N. Alexandrov National Cancer Centre of Belarus in Minsk said in a statement.

Elenagen contains a protein called p62/SQSTM1 that reduces chronic inflammation and triggers an immune response against tumors.

The drug's effect points to the value of "a fundamentally different therapeutic approach, one that supports the body's biology rather than simply intensifying chemotherapy,” Krasny said.

Treatment intervals ranged from less than one month to more than 30 months, with longer duration of treatment strongly correlated with longer survival following treatment discontinuation, they also found.

The company said it is planning larger trials in the U.S.

Details from the trial were published in the International Journal of Gynecologic Cancer and will be presented at the European Society of Gynaecological Oncology meeting in Copenhagen.

Researchers have designed an artificial intelligence tool that in early testing more accurately predicted a potentially fatal pregnancy complication often missed by current screening methods.

The condition, placenta accreta spectrum, occurs when the placenta attaches too deeply to the uterine wall and doesn't detach after birth, leading to heavy bleeding after delivery and sometimes to hysterectomy and even death.

Only about 30% of cases are diagnosed in advance because it can be missed on ultrasound exams, the developers of the new tool noted in a presentation at the Society of Maternal-Fetal Medicine meeting in Las Vegas.

Analyzing ultrasonography data obtained during pregnancy in 113 women at risk because of a previous cesarean section or some other predisposing factor, the AI program was able to correctly identify all cases of PAS and 75% of pregnancies without PAS. 

Overall, 82% of those who tested positive actually had the condition, while everyone who tested negative was free of it.

“Our team is very excited about the potential clinical implications of this model for accurate and timely diagnosis of PAS,” study leader Dr. Alexandra Hammerquist from the Baylor College of Medicine in Texas said in a statement.

Women in the study all gave birth at Texas Children’s Hospital between 2018 and 2025.

“Our next step is a prospective study in a more real-world setup,” said coauthor Dr. Hendrik Lombaard, also at Baylor.

This research could also lead to the development of a simple screening tool that could help identify women who may need a doctor's referral for a more detailed ultrasound, Lombaard added.

“We also want to expand the imaging to not just assist with screening but studying the potential to use it as a surgical planning tool,” Lombaard said.

Other teams are also developing AI tools for detecting PAS but so far, none have received approval from the U.S. Food and Drug Administration.