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Alzheimer’s Markers Predict Start of Mental Decline

Scientists at Washington University School of Medicine in St. Louis have helped identify many of the biomarkers for Alzheimer’s disease that could potentially predict which patients will develop the disorder later in life. Now, studying spinal fluid samples and health data from 201 research participants at the Charles F. and Joanne Knight Alzheimer’s Disease Research Center, the researchers have shown the markers are accurate predictors of Alzheimer’s years before symptoms develop.

“We wanted to see if one marker was better than the other in predicting which of our participants would get cognitive impairment and when they would get it,” said Catherine Roe, PhD, research assistant professor of neurology. “We found no differences in the accuracy of the biomarkers.”

The study, supported in part by the National Institute on Aging, appears in Neurology.

The researchers evaluated markers such as the buildup of amyloid plaques in the brain, newly visible thanks to an imaging agent developed in the last decade; levels of various proteins in the cerebrospinal fluid, such as the amyloid fragments that are the principal ingredient of brain plaques; and the ratios of one protein to another in the cerebrospinal fluid, such as different forms of the brain cell structural protein tau.

The markers were studied in volunteers whose ages ranged from 45 to 88. On average, the data available on study participants spanned four years, with the longest recorded over 7.5 years.

The researchers found that all of the markers were equally good at identifying subjects who were likely to develop cognitive problems and at predicting how soon they would become noticeably impaired.

Next, the scientists paired the biomarkers data with demographic information, testing to see if sex, age, race, education and other factors could improve their predictions.

“Sex, age and race all helped to predict who would develop cognitive impairment,” Roe said. “Older participants, men and African Americans were more likely to become cognitively impaired than those who were younger, female and Caucasian.”

Roe described the findings as providing more evidence that scientists can detect Alzheimer’s disease years before memory loss and cognitive decline become apparent.

“We can better predict future cognitive impairment when we combine biomarkers with patient characteristics,” she said. “Knowing how accurate biomarkers are is important if we are going to some day be able to treat Alzheimer’s before symptoms and slow or prevent the disease.”

Clinical trials are already underway at Washington University and elsewhere to determine if treatments prior to symptoms can prevent or delay inherited forms of Alzheimer’s disease. Reliable biomarkers for Alzheimer’s should one day make it possible to test the most successful treatments in the much more common sporadic forms of Alzheimer’s.

Study: Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later

Source: EurekAlert!

NCQA to Test Pioneering Way to Measure Quality, Foster Wider Use of Prevention Strategies

The National Committee for Quality Assurance (NCQA) and the Robert Wood Johnson Foundation (RWJF) recently announced a new approach to measuring quality that will provide a more sensitive gauge of risk factors and make it possible to create clinically meaningful incentives for providers to improve disease prevention.

Under a grant from RWJF, NCQA will evaluate a new measurement tool that focuses on improving the health outcomes of patients with heart disease and diabetes. The “Global Cardiovascular Risk” (GCVR) score, which is being co-developed by NCQA and Archimedes, Inc., is the “next generation” quality improvement tool that measures how well providers reduce the risk of future adverse outcomes—such as heart attacks, strokes, and diabetic complications—in the populations they serve. GCVR is also a powerful new use of electronic health records (EHRs), drawing upon clinical information from EHRs to provide the data needed to assess improvement in preventing bad outcomes.

“This new tool has the potential to become the first customized, outcomes-based electronic health record measure used by Medicare and commercial payers,” says NCQA President Margaret E. O’Kane. “Its widespread adoption could have a profound impact on health care costs because it assesses how well providers engage in prevention and goal-setting for their high-risk patients. We believe it could become the new gold standard of quality measurement, replacing some traditional measures that have been the cornerstone of quality improvement for years.”

The traditional approach to quality measurement focuses on processes of care, and reaching clinically artificial treatment goals for biomarkers, rather than the actual disease outcomes. Traditional approaches provide little quantitative information about the outcomes that actually occur based on the care patients receive. In contrast, the GCVR measures how much patients’ risk of future adverse health outcomes have been reduced. Unlike current measures, which focus on a particular process or biomarker, the GCVR measure is a single metric that captures what every provider can do to prevent adverse outcomes, all integrated in a medically and clinically realistic way.

Under the project, NCQA will:

  • Evaluate the feasibility of collecting data from EHRs to calculate a measurable result for different providers and provider organizations; and
  • Evaluate provider views on how useful and meaningful the GCVR score is for predicting risk.

“The GCVR program will change how providers, patients, and payers think about the measurement of quality and will provide much more accurate and effective incentives for preventing adverse outcomes than has been possible in the past,” says David Eddy, MD, PhD, founder of Archimedes Inc., a San Francisco-based healthcare modeling company. “Preventing bad outcomes is the ultimate purpose of the health care system, and this measure will directly address that goal,” he says. “And because bad outcomes cause expensive admissions, tests, and procedures, this new measure will be more effective in controlling costs, at the same time that it helps improve patients’ lives.”

“The GCVR is a game-changer for measuring quality, promoting prevention, and assessing the impact of health care decisions on patient outcomes,” says RWJF President and CEO Risa Lavizzo-Mourey, MD. “Measuring quality in this way could have major implications for improving patient care and lowering costs because this is focused on preventing adverse health outcomes, not just on care processes or goals, which has been the standard until now.”

Over the next 18 months, NCQA will evaluate the feasibility of extracting the electronic health data it needs to calculate the measure from a number of health systems and health plans that use EHRs from around the country. It is now in the process of recruiting organizations to participate. The data collection and analysis will occur over the summer and fall of 2013, and NCQA expects to report findings by summer 2014.

Watch the video A Pioneering Way to Measure Health Care Quality in which Helen Darling of The National Business Group on Health discusses how the GCVR will benefit employers.

Source: Robert Wood Johnson Foundation

New Study Proves Univfy IVF Prediction Tests More Accurate in Predicting IVF Success

Univfy Inc., a pioneer in predictive technology for health care and fertility, recently announced the publication of new research findings in Fertility & Sterility, validating the company’s Univfy PreIVF prediction tests as 1,000-times (likelihood scale) more powerful in predicting the probability of live birth in the first in vitro fertilization (IVF) treatment compared to estimates based on a woman’s age.

The peer-reviewed paper, “Personalized Prediction of First-Cycle In Vitro Fertilization Success,” shows that 86 percent of cases analyzed had significantly different probabilities of success compared to age-based estimates, and nearly 60 percent had a higher probability of live birth based on an analysis of the patients’ complete reproductive profiles. In fact, using the Univfy PreIVF prediction model, 42 percent of patients were found to have a personalized predicted success rate greater than 45 percent, while the age-control model could not differentiate these patients from others in the population.

Proven Accuracy Based on Personalized Prediction

The study is the first to validate that patient data available prior to starting IVF can be used to predict a patient’s chance of success to help her decide whether to pursue a first IVF treatment. The Univfy PreIVF test is an online data test that analyzes each individual’s fertility profile (including age, Body Mass Index (BMI), Day 3 FSH, semen analysis, and prior fertility and medical history) and compares it against data from thousands of IVF cycles to instantly deliver personalized prognosis of IVF success. The retrospective validation study analyzed anonymized IVF data aggregated from more than 13,000 first IVF cycles from three university-affiliated outpatient IVF clinics in the U.S., Canada and Spain.

Personalized Prediction of IVF Success Helps Patients

“Our research findings allow us to use known clinical predictors with much greater predictive power to support patients who are considering IVF for the first time,” said Mylene Yao, M.D., CEO and co-founder of Univfy. “Not knowing their personal chances of IVF success may cause many women to be missing out on a treatment that could be highly effective for them.”

While a higher likelihood of success is welcome news for many couples, the study also suggests predictions based on age alone, or age plus a few factors, could falsely reassure a small percentage of patients. Based on the predicted probability, the Univfy PreIVF test also reports the percentile of a patient’s chances of success, which provides a more balanced perspective to the patient and her doctor.

“An accurate prognosis is equally important for those whose likelihood of success is quite high and for those whose chances are much lower than age-based predictions,” Dr. James Grifo, Program Director of the New York University Fertility Center and Director of the Division of Reproductive Endocrinology and Professor of Obstetrics and Gynecology at the NYU School of Medicine. “Predicting the chances of IVF success for each patient may also support physicians in refining clinical protocols to improve care.”

“More accurate personalized prognoses of potential live birth outcomes with IVF can guide both patients and their physicians with treatment decisions,” said Dr. Gedis Grudzinskas, Consultant in Infertility and Gynaecology at 92 Harley Street, London Bridge Hospital, Princess Grace Hospital and Woodlands Health Centre, London, UK, and Editor of Reproductive Biomedicine Online, an international journal devoted to biomedical research on human reproduction.

Enhancing Care through Predictive Analytics

Previously, advanced predictive modeling that is rigorously validated was not accessible to patients and the broader medical community. Univfy has integrated these research processes with proprietary, analytics-powered platforms to deliver scientifically validated predictive information via a user-friendly interface to patients and providers. The Univfy platforms can also serve point-of-care prognostics or administrative needs in other areas of healthcare, outside of reproductive medicine.

Univfy offers complimentary and confidential analysis to any clinic interested in learning how closely their patient-specific success rates compare to the Univfy PreIVF model. This analysis is feasible even for small or mid-size fertility clinics.

Based on its proven model, Univfy offers two prediction tests for consumers: the Univfy PreIVF for women considering IVF for the first time, and the Univfy PredictIVF for women who have had IVF and are considering another IVF treatment. Both are online tests that patients complete in the privacy of their own home by simply entering their own individual health data. The tests are also available for use in physician offices via Univfy’s clinic platform through a business-to-business model. Semi-customization of prediction tests is also available upon request.

Study: Personalized prediction of first-cycle in vitro fertilization success

Source: Univfy

Merck and Regenstrief Institute Establish Evidence-Based Care Collaboration

The Regenstrief Institute and Merck, known as MSD outside the United States and Canada, have signed a five-year agreement to collaborate on a range of projects that will use clinical data to inform personalized delivery of health care. The work will explore novel methods for studying diseases and interventions for chronic conditions such as diabetes, cardiovascular disease and osteoporosis.

Generation Scotland, Arrayjet Partner to Develop New Products and Services for Biomarker Identification and Development.

Generation Scotland (GS) and Arrayjet Ltd are pleased to announce a new collaboration. The project builds on the complementary strengths of Generation Scotland and Arrayjet; combining high quality research, human biobank material and health data with cutting edge inkjet microarray technology.