News
Study unveils ‘groundbreaking’ insights into metastatic breast cancer management
Swiss start-up OncoGenomX has compared two algorithms for managing metastatic, hormone receptor-positive breast cancer

A new study has shed light on the challenges of over-treatment and under-treatment in breast cancer management, in a move that could pave the way for a new era in cancer care.
Over-treatment in cancer arises from various factors, including physicians’ legal concerns, patient anxiety, and the fervour for cutting-edge therapies. Conversely, under-treatment is often rooted in healthcare access disparities and socioeconomic factors.
The Swiss start-up OncoGenomX has undertaken an initiative, comparing two algorithms for managing metastatic, hormone receptor-positive breast cancer – a type of breast cancer that grows with the help of one or both of the female hormones oestrogen and/or progesterone, affecting an area of the body beyond the breast.
In the study, the ASCO algorithm, adhering to American Society of Clinical Oncology (ASCO) recommendations, has been found to potentially lead to suboptimal treatment for 56 per cent of patients, corresponding to an expenditure of US$9.4m a year for 200 patients.
The OncoGenomX investigational PredictionStar algorithm, which aims to individualise treatments based on tumour response predictions, has been found to incur 20 per cent higher expenses (US$23m) and reduce the risk of suboptimal treatment from 56 per cent to 15 per cent. The cost increase is offset by threefold savings on suboptimal anticancer drugs.
The company says the findings are critical in the light of the rising financial burdens associated with cancer care, particularly for patients with metastatic breast cancer and the healthcare system as a whole.
Wolfgang Hackl, CEO of OncoGenomX, highlights a significant revelation in metastatic breast cancer treatment.
He says: “Historically, under- and over-treatment were considered as separate concerns, but our study underscores an undiscovered connection between them.
“The PredictionStar approach not only alleviates financial burdens on both the healthcare system and patients but can also be expected to improve treatment outcomes.
“Ongoing research is committed to verifying and expanding upon these hypotheses, shedding light on the efficacy and cost implications of the PredictionStar method.”
Insight
Early PET scan could chemo response in aggressive breast cancer – study
News
Femtech World reveals startup of the year shortlist

We are excited unveil the three finalists competing for one of the Femtech World Awards’ most coveted honours: the Startup of the Year Award, sponsored by Future Fertility.
This award celebrates an early-stage company making a bold impact in women’s health through innovation, vision and execution.
The winner will be announced at our virtual ceremony on 19 June, with the decision made by a representative from category sponsor Future Fertility.
Congratulations to the shortlist and thank you to everyone who entered or nominated.
Startup of the Year Shortlist

Hello Inside is the first women’s health AI company to turn daily metabolic signals into outcomes women feel and healthcare systems reimburse.
Women’s health has long been under-researched, and current AI benchmarks fail on women’s health questions roughly sixty percent of the time.
Hello Inside built the architecture to close that gap.
Across four years and 12,000+ validated metabolic profiles, three in four women improve at least one symptom within ninety days.
They lose four kilograms in three months, moving from overweight into the healthy range. In a clinical study with Alisa Vitti’s Flo Living, 91.9 per cent reduced PMS burden within sixty days.


U-Ploid is an early-stage biotechnology company tackling one of the most fundamental challenges in fertility care: the sharp, age-related decline in egg quality that limits outcomes across IVF and egg freezing.
While much of the field focuses on improving assessment and selection, U-Ploid is developing a first-in-class therapeutic approach designed to improve egg quality itself by addressing the biological causes of age-related chromosomal errors.
Supported by strong preclinical evidence and now advancing into human studies, U-Ploid combines scientific rigour, regulatory discipline and long-term vision to help redefine what is possible in fertility care.
News
Gestational diabetes increases risk of type 2 diabetes – even at normal weight, study finds

Gestational diabetes is a strong risk factor for future type 2 diabetes, even in women with normal pre-pregnancy weight, according to a study at the University of Gothenburg.
The researchers call for earlier testing and better follow-up.
“Our results show that gestational diabetes functions as a kind of stress test for the body’s ability to manage blood sugar, and identifies women with a greatly increased risk of future type 2 diabetes”, said Jon Edqvist, PhD and affiliated to research at the University of Gothenburg, and operating room nurse at Sahlgrenska University Hospital.
Gestational diabetes is a special type of diabetes that can affect pregnant women.
The condition is defined as elevated blood sugar levels, without previously known diabetes. Treatment involves self-monitoring of blood sugar, advice on lifestyle habits and, if necessary, medication.
Identifying gestational diabetes is important because the disease increases the risk of complications such as preeclampsia, the need for a cesarean section and high birth weight for the baby.
Those who have had gestational diabetes are also at higher risk of later developing type 2 diabetes.
In the current study, published in eClinicalMedicine, researchers now show that gestational diabetes is a strong indicator of future risk of developing type 2 diabetes, even in women with normal weight before pregnancy.
Elevated risk even with normal weight
The study is based on data from the Medical Birth Registry on just over 1.15 million first-time mothers in Sweden, who gave birth between 1987 and 2019. 16,870 women with confirmed gestational diabetes were compared with age-matched women without the diagnosis. The median follow-up period was nine years.
The results show that women with a BMI of 35 and above, i.e. severe obesity, had an almost tenfold increased risk of developing gestational diabetes compared to women with normal weight.
The risk of subsequent type 2 diabetes also increased with higher BMI, but it was significantly increased even with normal weight, which the researchers describe as particularly worrying.
More follow-up and more studies
The researchers behind the study welcome the recently updated recommendations on gestational diabetes in Sweden, where a higher proportion of pregnant women at increased risk are expected to be offered testing earlier in pregnancy, and if necessary, interventions.
“Diagnostics and care of gestational diabetes have looked very different in different parts of the country,” said Annika Rosengren, professor at the University of Gothenburg.
“There is a need for both improved follow-up after gestational diabetes, and more studies that investigate how such follow-up affects future health and prognosis”
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