Disease Management
We have experience in many therapeutic areas, including
oncology, diabetes, diabetes-related disorders,
respiratory syncytial virus, as well as point-of-care
diagnostic technology. See our Case Studies below.
Oncology
Anemia is a widespread problem in the cancer population
and has important clinical consequences including an
impact on quality of life. Good management of anemia in
the cancer population is therefore, essential. With
extensive experience in anemia management studies,
Epsilon was in a unique position to provide research
support to our client in understanding anemia related to
cancer in Europe. The European Cancer Anemia Survey (ECAS)
was developed in an effort to give oncologists
throughout Europe an overview of the current practice of
anemia management in cancer populations.
Challenge
Guidelines for the treatment of cancer-related anemia
were in early acknowledgment and development, however
not consistently implemented into the standard of cancer
care. Human recombinant epoetin alpha (epoetin), an
erythropoiesis-stimulating protein, had been developed
to reduce the need for allogenic blood transfusions in
anemic patients (hemoglobin >10mg/dL and <12mg/dL) The
successful clinical experience in treating chronic
anemia related to kidney disease with epoetin suggested
that anemia related to other disease might respond as
well.
Solution
Epsilon assisted our client in conducting ECAS, a large,
multinational prospective survey defining the
prevalence, incidence, and treatment of anemia in cancer
patients. 15,367 patients were enrolled from 748 cancer
centers in 24 European countries over 12 months.
Study Overview
ECAS was a prospective survey that tracked anemia
management for up to 6 months in an adult cancer
population. It includes different patients at various
points within their states of disease severity and
treatment. Both patients receiving treatment
(chemotherapy, radiotherapy, concomitant
chemo-radiotherapy) and patients in follow-up are
targeted in this survey.
The main objective of ECAS was to create an extensive
and valid European database documenting the severity of
anemia and its management in the cancer population,
focusing also on treatment policies and protocols
currently used in the centers across Europe. A further
objective of ECAS was to delineate patient
characteristics, tumor types and intensities of cancer
treatment that lead to anemia. Additionally, ECAS aimed
to develop models predicting those patients who are most
at risk for anemia and for whom treatment will be most
effective.
Integration of Resources
Epsilon utilized a variety of data collection tools to
support the wide range of capabilities of the some 1,000
participating cancer investigators. Teleform® scanning
software input survey data into Epsilon proprietary
AWARE software was developed utilizing SPSS statistical
software package, v 9.0, and Microsoft Excel® and
Powerpoint®.
Results
Using the largest cancer treatment database of European
patients ever, Epsilon statisticians performed
predictive risk modeling to determine patient
characteristics which increase risk for developing
anemia, and when a physician could expect to see anemia
develop. This predictability of anemia and the treatment
gap revealed an opportunity for our client to provide
anemia treatment to a large European population, and
contributed to European best practice guidelines for
cancer therapy.
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Diabetes Related Disorders
The prevalence of type 2 diabetes mellitus is rising
rapidly in all developed countries, particularly in the
growing population of persons >50 years of age. As a
dangerous consequence, this is accompanied by a
proportionate increase in the incidence of chronic renal
disease. Evidence-based medicine has shown that tight
blood glucose control can delay the onset and retard the
progression of diabetic complications, and while it is a
challenge to closely manage the complexity of diabetes,
it is more difficult to effectively treat the multiple
associated comorbidities that develop.
Challenge
The implications of providing electronically prompted
best practice guidelines to clinicians for their care of
patients with type 2 diabetes and comorbidities are
immense. Timely access to recommended clinical targets
and treatment algorithms that guide medication
adjustment is likely to improve clinician’s
implementation of best practice guidelines for
prognostically relevant comorbidities. In addition to
well-established prognostic risk factors like
hypertension, glycemic control, hyperlipidaemia, and
progression of renal disease, anaemia in diabetic
patients has been recently described as an often
unrecognized and untreated comorbid disease.
Solution
Best practice guidelines support early intervention and
aggressive treatment of hypertension, hyperglycaemia,
proteinuria, hypercholesterolemia, and anaemia. To date,
guideline-based management has been proven to be
difficult.
Epsilon assisted our client with the development of
treatment algorithms to facilitate the use of current
best practice guidelines for the management of frequent
comorbid diseases and established risk factors in the
treatment of type 2 diabetes associated with chronic
kidney disease.
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Point-of-Care
Diagnostic Technology
Evidence that glycemic control in critically ill
hospitalized patients improves outcomes continues to
accumulate. While standardized protocols in the
intensive care unit (ICU) are known to reduce
variability of practice and improve outcomes through
consistent implementation, a striking aspect of these
protocols is the variability in insulin delivery method
(subcutaneous vs. intravenous), hyperglycemia threshold,
and frequency of monitoring, insulin dose to blood
glucose ratios and the complexity of instructions. These
can result in great differences in insulin dosing,
variable success in treatment to normal glycemia, and
higher incidence of hypoglycemia, as well as confusion
and potential error for those trying to implement the
protocol.
Challenge
To date, few institutions have been able to achieve the
standards for inpatient glycemic control recommended by
the American Association of Clinical
Endocrinologists/American College of Endocrinology (AACE),
however much progress has been made. Limited access to
blood glucose is one factor makes it difficult for
clinicians to measure progress towards glycemic control.
The “lack of integrated
that allow tracking and trending of glycemic control and
hypoglycemia metrics” is cited as a barrier that
challenges the installation of glycemic control
programs. The recommendations from AACE have called for
a more effective use of clinical data for quality
control and policy-making purposes and advocate
formulation of “...a system to track hospital glucose
data on an ongoing basis to be able to assess the
quality of care delivered.
Solution
To address this need, Medical Automation Systems
(Charlottesville, VA) developed the Remote Automated
Laboratory System-Tight Glycemic Control Module (RALS®-TGCM).
Study Overview
Epsilon was tasked to conduct the Glucose Control
Outcomes Study (GluCOS) to measure the value that RALS-TGCM
brings to healthcare professionals implementing and
monitoring glycemic control protocols. GluCOS was an
observational, comparison case study conducted in 10
U.S. hospitals. Point-of-care glucose data from each
participating hospital were retrieved for evaluating
average blood glucose values following the installation
of RALS-TGCM.
Results
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The GluCOS results revealed that RALS-TGCM offers
many important benefits to the hospital setting
including:
Eight out of the 10 participating hospitals
experienced statistically significant improvement
(decrease) in their levels after RALS-TGCM was
implemented.
-
Of the 8 hospitals that experienced improvement, the
reduction in mean blood glucose values ranged from
11.4 to 2.2 mg/dL, with an average decrease of 4.2
mg/dL (p<0.001). (See Figure 1.)
-
Overall, after RALS-TGCM implementation, there was a
higher proportion of values in the target range of
70–110 mg/dL (from 30.1% pre-installation to 39.8%
post-installation). (See Figure 2.)
Figure 1. Mean Blood Glucose Values Before & After RALS-TGCM
Installation.
Figure 2. Proportion of Blood Glucose Values in Target
Range 70-110 (mg/dL) before and after RALS-TGCM
Installation.
