Download Quality-adjusted-life-years-with-a-focus-on

Quality adjusted life years with a
focus on
studies about chronic hepatitis C
(HCV)
A seminar report presentation
by:
Viktorija Labroska
Anita Pechenkovska
Input parameters used for drug
effectiveness and quality of life of
patients
• A Markov simulation model of CHC disease progression is used to
evaluate the cost-effectiveness of different treatment strategies
based on genotype. The model calculates the expected lifetime
medical costs and quality adjusted life years (QALYs) of hypothetical
cohorts of identical patients receiving certain treatments.
• Treatments are compared based on the ratio of the additional cost
of the more costly treatment divided by the additional effectiveness
of the treatment. Reference patient cohorts are defined according
to the average characteristics, gender and age, obtained from the
trials used in this study (52-years old, 64 % male, treatment-naïve
who have CHC with or without cirrhosis).
As input parameters are used the type of genotype, the type of
treatment, duration of the treatment, SVR (%) , and clinical trials.
Randomized controlled trials
• What is randomized clinical trial?
Randomized clinical trials are scientific
investigations that examine and evaluate the
safety and efficacy of new drugs or
therapeutic procedures using human subjects.
• In a randomized clinical trial, patients and trial
personnel are deliberately kept unaware of
which patient is on the new drug.
Types of clinical trials?
• Clinical trials vary depending on who is
conducting the trial.
• Pharmaceutical companies typically conduct trials
involving new drugs or established drugs in
disease areas where their drug may gain a new
license.
• The pharmaceutical industry has adopted a
specific trial classification based on four clinical
phases of development of a particular drug
(Phase I-IV)
• -In Phase I, manufactures usually test the effects of a new drug in
healthy volunteers or patients unresponsive to usual therapies.
They look at how the drug is handled in the human body
(pharmacokinetics/pharmacodynamics ).
• -In Phase II, examine dose-response curves in patients and what
benefits might be seen in a small group of patients with a particular
disease.
• -In Phase III, a new drug is tested in a controlled fashion in a large
patient population against a placebo or standard therapy. A positive
study in Phase III is often known as a landmark study for a drug,
through which it might gain a license to be prescribed for a specific
disease.
• -In Phase IV, the study is often called a postmarketing study as the
drug has already been granted regulatory approval/license. These
studies are crucial for gathering additional safety information from
a larger group of patients in order to understand the long-term
safety of the drug and appreciate drug interactions.
Classification by design:
• This classification is more descriptive in terms how patients are
randomized to treatment
• -Parallel-group trial – patients are randomized to the new
treatment or to the standard treatment and following-up to
determine the effect of each treatment in parallel group.
• -Crossover trials randomize patients to different sequences of
treatments, but all patients eventually get all treatments in
varying order.
• -Factorial trials assign patients to more than one treatmentcomparison group.
• -Cluster randomized trials are performed when larger groups
are randomized instead of individual patients.
Why might clinical trial results not
represent the true difference?
• Reasons for erroneous results fall into three
main categories:
• • Firstly, the trial may have been biased in
some predictable fashion.
• • Secondly, it could have been contaminated
(confounded) by an unpredictable factor.
• • Thirdly, the result might simply have
occurred by random chance.
Clinical trail endpoints
• What is a clinical trial endpoint?
A clinical trial endpoint is defined as a measure
that allows us to decide whether the null
hypothesis of a clinical trial should be accepted or
rejected.
• In a clinical trial, the null hypothesis states that
there is no statistically significant difference
between two treatments or strategies being
compared with respect to the endpoint measure
chosen.
Clinical trial endpoints can be classified
as primary or secondary endpoints.
• -Primary endpoints measure outcomes that will answer the primary
(or most important) question being asked by a trial.
Ex.Whether a new treatment is better at preventing disease-related
death than the standard therapy. The primary endpoint would be
based on the occurrence of disease-related deaths during the
duration of the trial.
• - Secondary endpoints ask other relevant questions about the same
study.
Ex. Whether there is also a reduction in disease measures other than
death, or whether the new treatment reduces the overall cost of
treating patients.
• -Co-primary endpoints – when secondary endpoints are also
important as the primary endpoints.
What are the main types of
endpoints?
An endpoint may be based on:
• a binary clinical outcome indicating whether an event–
such as death from any cause – has occurred
• death from a disease-specific cause (eg, a fatal stroke
for a trial comparing blood pressure treatments)
• the occurrence of disease signs or symptoms
• the relief of symptoms
• quality of life while disease is active
• the use of healthcare resources (eg, the number of
hospital admissions)
Composite endpoints
Advantages of using composite endpoints:
There are two main advantages of using a composite
endpoint.
• An endpoint with multiple outcomes means that more
outcome events will be observed in total. Since the number
of patients needed in the trial decreases as the number of
events occurring in the control group increases, a
composite endpoint allows us to evaluate a new treatment
by using a smaller number of patients in the trial.
• The other advantage of combining several outcomes is that
a more comprehensive evaluation of a treatment can be
given across more than just one category of outcome.
Limitations of composite endpoints:
• In a composite endpoint of multiple outcomes we
make the assumption that avoiding any one outcome
has an equal importance as avoiding any other
outcome.
• The second assumption made when using composite
endpoints is that all individual outcome measures are
related to the disease process and are equally
meaningful.
• An additional limitation of composite endpoints is that
they can also give inconsistent results, with certain
outcomes improving and others worsening, making
overall interpretation of the study difficult.
Surrogate endpoints
•
•
•
•
•
It is not always practical or feasible to base endpoints on ‘true’ clinical outcomes
that, like death, might only occur after some time. Therefore, to be able to assess
potential treatment effects, alternative measures are needed. One solution that
has recently been attracting interest is surrogate endpoints.
A potential surrogate endpoint should be chosen based on strong biological
rationale. Commonly used surrogate endpoints include:
pharmacokinetic measurements, such as concentration–time curves for a drug or
its active metabolites in the bloodstream
in vitro measurements, such as the mean concentration of an antibiotic agent
required to inhibit growth of a bacterial culture
radiological appearance, such as increased shadowing seen on a chest X-ray film of
a patient with smoking-related lung disease that is related to a patient’s breathing
capacity.
• a change in the levels of disease markers, such as a change in blood pressure as a
predictor of a future occurrence of a stroke or kidney disease
the macroscopic appearance of tissues, such as the endoscopic visualization of an
area of erosion in the stomach that is considered by gastroenterologists to be the
precursor of stomach bleeds.
• Advantages of surrogate endpoints:
Use of a surrogate endpoint can reduce the
sample size needed for a study and thereby
the duration and cost of performing a clinical
trial.
Surrogate endpoints are particularly useful
when conducting Phase II screening trials to
identify whether a new intervention has an
effect, since a change is often seen in a
surrogate endpoint long before an adverse
event occurs.
• Limitations of surrogate endpoints:
Surrogate endpoints are only useful if they are
a good predictor of a clinical outcome.
If this relationship is not clearly defined,
surrogate endpoints can be misleading.
Health-economic endpoints
• Health economics and technology are done to
compare the quality of life or patients in different
treatment group or the costs of care of new
treatments (which are usually more expensive
than standard treatments).
• There are two main measures of health
economics: quality-adjusted life-years (QALYs)
gained – a measurement of the duration of an
individual’s life, taking into account the wellbeing that they experience during that time – and
cost.
• Advantages of health-economic endpoints:
 By calculating the cost per QALY gained for
different treatments, healthcare providers can
compare where best to invest their limited
resources
• Limitations of health-economic endpoints:
 The data captured for an economic analysis might
not even be used if the treatment is both more
expensive and less effective than standard care.
 Economic analyses might not be easily
transferable across countries since the cost of
care can be very different internationally
Intention to treat analysis
• An approach to post-randomization data analysis
of clinical trials.
• A presentation of the results of a clinical trial
obtained from data of all subjects not only from
those who adhered fully to their assigned
treatment protocol.
• Comparing all trial subjects according to the
treatment groups in they were initially
randomized, regardless of treatment compliance,
or any treatment subsequently received.
Even though this approach might not capture the full potential benefit of a certain
therapy, still it is a useful method for minimizing the inclination or prejudice for the
results.
 It ignores noncompliance, protocol deviations, withdrawal, and anything that
happens after randomization.
• An ITT analysis uses the information from all the subjects in
a trial at any given time point in the study, which enables an
interim analysis to be performed.
• The ITT analysis can identify a possible bias (a conclusion
that may be incorrect).
• ITT analysis uses the information from all the subjects in a
trial at any given time point in the study even also
analysis of data that is conducted before data collection has
been completed.
• ITT takes into an account the administration of the
treatment.
Dissadvantages:
• The ITT analysis does not aim to determine the maximum potential
effectiveness of a treatment.
• might not show a statistically significant benefit, or might show the
benefit to be smaller.
Intention to treat analysis vs. perprotocol (PP) analysis
• PP or perprotocol analysis represents an
alternative method of analysis which excludes
subjects who were not fully compliant with the
study protocol
• it is an efficacy analysis /analysis by treatment
administered.
• The PP analysis attempts to remove the effects of
variable compliance patterns.
• The IPP approach depicts real-life situations
better than the per-protocol (PP) method;
PP gives slightly more significant results than
ITT
 PP results are much more significant than ITT
 PP results are not significant, but ITT are –
confounding?
 ITT analysis is not significant, PP results are crossover
Design and the results of the study that was
used for determination of utility values and
used questionnaires
• Utilities = values that reflect individual’s preferences for one
health state that is of interest and in our case for chronic
hepatitis C (HCV) and evaluation of different health
outcomes.
• The health utilities are measured on an interval scale with
zero reflecting states of health equivalent to death.
• The evaluation of the utilities is typically combined with
survival estimates and aggregated across individuals to
generate quality-adjusted life years (QALYs) for use in cost–
utility analyses of healthcare interventions.
• To see the influence of the mentioned health-state on the
health but on the society factors too.
- for studying the utilities were used indirect methods for
utility measurement
- by applying utility algorithms to questionnaires and by
mapping from a disease-specific health-related quality of life
(HRQoL) instrument onto the utility algorithm of a generic
instrument such as the EQ-5D (EuroQol five dimension).
• All patients completed
three instruments:
- Health Utility Index
Mark 2 (scores 0–1),
-Short Form-36 (scale
scores 0–100), and
-a disease-specific healthrelated quality of life
instrument (Chronic Liver
Disease Questionnaire;
scores 1–7)
The participants valued a limited number of health states and a scoring algorithm was
developed using econometric modelling (EQ-5D and SF-6D) or a multiplicative multiattribute utility function (HUI) to predict utilities for other health states not directly
valued. Patients then completed a simple questionnaire which defines the generic
health state they are in, and the appropriate utility from the scoring algorithm is applied.
• Medical Outcomes Study Short Form 36 (SF- 36)
contains 36 items divided into eight domains.
-physical functioning;
-role limitations due to physical health;
-role limitations due to emotional problems;
-energy/fatigue;
-emotional well-being;
-social functioning; pain;
-general health.
Both domain scores and summary scores (mental component
summary [MCS] and a physical component summary [PCS]) were
obtained.
Domain scores for SF-36 range from 0 and 100 (0 representing a very
low level of QoL in that item and 100 representing a very positive
response to that item),
• Health Utility Index (Mark 2),
a self-administered 15-item questionnaire that
assesses health status.
Health status assessments were then converted
into utility scores according to community
preferences, providing an overall utility score
between 1.00 (perfect health) and 0.00 (dead).
HRQL (Health-related quality of life) instrument
specifically designed for patients with liver disease, the Chronic Liver Disease Questionnaire
(CLDQ).
Includes 29 items divided into six domains:
- Abdominal Symptoms (AS),
- Activity (AC),
- Emotional Function (EF),
- Fatigue (FA),
- Systemic Symptoms (SS),
-Worry (WO).
• Utilities allow a direct comparison of the loss of qualityadjusted life years across patients with different conditions.
• Utilities are suitable for economic analyses that compare
different interventions in patients with chronic liver disease.
• In the mentioned study we observed strikingly high
correlations between utility measures and most domains of
both a generic (SF-36) and a liver disease specific HRQL
measure (CLDQ).