Biostatistics Flashcards
1
Q
What is statistics?
A
Statistics involves the collection and analysis of all types of data
2
Q
What is biostatistical analysis or biostatistics?
A
When statistics are used to understand the effects of a drug or medical procedure on people and animals, the statistical analysis is called biostatistical analysis or biostatistics
3
Q
What is the path to publication for the classic type of research study?
A
Begin with a research question, design the study, enroll the subjects, collect the data, analyze the data and publish
4
Q
What happens after a study manuscript is published?
A
A study manuscript can be submitted for publication in a professional, peer-reviewed journal. The editor of the journal selects potential publications and sends them to experts in the topic area for peer review
5
Q
What is the intention of peer review?
A
Peer review is intended to assess the research design and methods, the value of the results and conclusions to the field of study, how well the manuscript is written and whether it is appropriate for the readership of the journal
6
Q
What is the potential impact of a peer reviewed study manuscript?
A
The reviewers make a recommendation to the editor to either accept the article (usually with revisions) or reject it. Data that contradicts a previous recommendation, or presents new information, can change treatment guidelines
7
Q
Describe the organization of a published clinical trial
A
A published clinical trial begins with an abstract that provides a brief summary of the article. The introduction to the study comes next, which includes background information, such as disease history and prevalence, and the research hypothesis. This is followed by the study methods, which describe the variables and outcomes, and the statistical methods used to analyze the data. The results section includes figures, tables and graphs. A reader needs to interpret basic statistics and common graphs in order to understand the study results. The researchers conclude the article with an interpretation of the results and the implications for current practice
8
Q
What is continuous data?
A
Continuous data has a logical order with values that continuously increase (or decrease) by the same amount. Data is provided by some type of measurement which has unlimited options (theoretically) of continuous values
9
Q
What is the two types of continuous data and what is the difference between them?
A
The two types of continuous data are interval data and ratio data. The difference between them is that interval data has no meaningful zero (zero does not equal none) and ratio data has a meaningful zero (zero equals none)
10
Q
What is discrete (categorical) data and what are the two types?
A
The two types of discrete data, nominal and ordinal, have categories, and are sometimes called categorical data. Data fits into a limited number of categories
11
Q
What is nominal data?
A
With nominal data, subjects are sorted into arbitrary categories and order of categories does not matter
12
Q
What is ordinal data?
A
Ordinal data is ranked and has a logical order. Ordinal scale categories do not increase by the same amount
13
Q
What are descriptive statistics and what are the typical descriptive values?
A
Descriptive statistics provide simple summaries of the data. The typical descriptive values are called the measures of central tendency, and include the mean, the median and the mode
14
Q
What is the mean?
A
The mean is the average value and is calculated by adding up the values and dividing the sum by the number of values. The mean is preferred for continuous data that is normally distributed
15
Q
What is the median?
A
The median is the value in the middle when the values are arranged from lowest to highest. When there are two center values (as with an even number of values), take the average of the two center values. The median is preferred for ordinal data or continuous data that is skewed (not normally distributed)
16
Q
What is the mode?
A
The mode is the value that occurs most frequently. The mode is preferred for nominal data
17
Q
What are the two common methods of describing the variability?
A
Range and standard deviation
18
Q
What is the range?
A
The range is the difference between the highest and lowest values
19
Q
What is the standard deviation?
A
Standard deviation indicates how spread out the data is, and to what degree the data is dispersed away from the mean. A large number of data values close to the mean has a smaller SD, Data that is highly dispersed has a larger SD.
20
Q
What do large sample sets of continuous data tend to form?
A
A Gaussian or “normal” (bell-shaped) distribution
21
Q
Describe the curve of the Gaussian distribution when the distribution of data is normal.
A
When the distribution of data is normal, the curve is symmetrical (even on both sides), with most of the values closer to the middle. Half of the values are one the left side of the curve, and half of the values are on the right side. A small number of values are in the tails.
22
Q
Describe the data when it is normally distributed with the Gaussian distribution?
A
- The mean, median and mode are the same value and are at the center point of the curve
- 68% of the values fall within 1 SD of the mean and 95% of the values fall within 2 SDs of the mean
23
Q
Describe how the curve of normally distributed data changes based on the spread (or range) of the data
A
The curve gets taller and skinnier as the range of data narrows. The curve gets shorter and wider as the range of data widens (or is more spread out).
24
Q
What happens when the data is skewed?
A
Data that are skewed do not have the characteristics of a normal distribution; the curve is not symmetrical, 68% of the values do not fall within 1 SD from the mean and the mean, median and mode are not the same value
*This usually occurs when the number of values (sample size) is small and/or there are outliers in the data
25
What is an outlier?
An outlier is an extreme value, either very low or very high, compared to the norm
*When there are a small number of values, an outlier has a large impact on the mean and the data becomes skewed
26
What is the best measure of central tendency when there are outliers?
In this case, the median is a better measure of central tendency
27
Describe what it means when the data is skewed to the left or the right.
Data is skewed towards outliers. When there are more low values in a data set and the outliers are the high values, data is skewed to the right (positive skew). When there are more high values in the data set and the outliers are the low values, the data is skewed to the left (negative skew)
28
What is a variable?
A variable in a study is any data point or characteristic that can be measured or counted
29
What is an independent variable and dependent variable?
An independent variable is changed (manipulated) by the researcher in order to determine whether it has an effect on the dependent variable
30
How does a trial show that a product is significantly better than the current treatment or placebo?
To show significance, the trial needs to demonstrate that the null hypothesis is not true and should be rejected, and the alternative hypothesis can be accepted
31
What is a null hypothesis?
A null hypothesis states that there is no statistically significant difference between groups. The null hypothesis is what the researcher tries to disprove or reject
32
What is the alternative hypothesis?
The alternative hypothesis states that there is a statistically significant difference between the groups. The alternative hypothesis is what the researcher hopes to prove or accept
33
What is the alpha level?
Alpha is the maximum permissible error margin. Alpha is the threshold for rejecting the null hypothesis
34
What is the most common alpha in medical research?
In medical research, alpha is commonly set at 5% (or 0.05)
35
If a smaller alpha value is chosen, what is required?
A smaller alpha vale can be chosen, but this requires more data, more subjects (which means more expense) and/or larger treatment effect
36
What is the p-value and how is it important?
The p-value is compared to alpha. If alpha is set at 0.05, and the p-value is less than 0.05, the null hypothesis is rejected, and the result is termed statistically significant. If the p-value is greater than or equal to alpha (P>0.05), the study has failed to reject the null hypothesis, and the result is not statistically significant
37
What is a confidence interval?
A confidence interval (CI) provides the same information about significance as the p-value, plus the precision of the result
38
What is the relationship between confidence interval and alpha?
CI = 1 - a
*If alpha is 0.05, the study reports 95% CIs, an alpha of 0.01 corresponds to a CI of 99%
39
Describe how the values in the CI range are used to determine whether significance has been reached.
When comparing difference data, the result is statistically significant if the CI range does not include 0. When comparing ratio data, the result is statistically significant if the CI range does not include one
40
What can a confidence interval tell?
A CI indicates that you are 95% confident that the true value lies somewhere within the range given
41
What do narrow and wide CI ranges imply?
A narrow CI range implies high precision and a wide CI range implies poor precision
42
Describe type I errors
Type I errors are false positives where the alternative hypothesis was accepted and the null hypothesis was rejected in error
43
How is the probability or risk of making a type I error determined?
The probability, or risk, of making a type I error is determined by alpha and it relates to the confidence interval
*When alpha is 0.05 and a study result is reported with p<0.05, it is statistically significant and the probability of a type I error is <5%
44
Describe type II errors
Type II errors (denoted as beta) are false negatives where the null hypothesis is accepted when it should have been rejected
*Beta is set by the investigators during the design of a study and it is typically set at 0.1 or 0.2, meaning the risk of type II errors is 10% ad 20%
45
When does the risk of type II errors increase and how can you decrease this risk?
The risk of type II error increases if the sample size is too small. To decrease this risk, a power analysis is performed to determine the sample size needed to detect a true difference between groups
46
What is power and how is it calculated?
Power is the probability that a test will reject the null hypothesis correctly
Power = 1 - B
47
What does it mean when power increases?
As the power increases, the chance of a type II error decreases
48
How is power determined?
Power is determined by the number of outcome values collected, the difference in outcome rates between the groups and the significance (alpha) level
49
What is risk?
Risk refers to the probability of an event (how likely it is to occur) when an intervention is given and the lack of intervention is measured as the effect in the placebo (or control) group
50
What is relative risk?
The relative risk (RR) is the ratio of risk in the exposed group (treatment) divided by risk in the control group
51
How is risk calculated?
Risk = number of subjects in group with an unfavorable event/total number of subjects in group
52
How is relative risk calculated?
RR = risk in treatment group/risk in control group
53
What does it mean when RR = 1 (or 100%)?
Implies no difference in risk of the outcome between the groups
54
What does it mean when RR > 1 (or 100%)?
Implies greater risk of the outcome in the treatment group
55
What does it mean when RR < 1 (or 100%)?
Implies lower risk (reduced risk) of the outcome in the treatment group
56
What does the relative risk calculation determine?
The RR calculation determines whether there is less risk (RR < 1) or more risk (RR > 1)
57
What does the relative risk reduction (RRR) indicate?
The relative risk reduction (RRR) is calculated after the RR and indicates how much the risk is reduced in the treatment group compared to the control group
58
What is the RRR formula?
RRR = (% risk in control group - % risk in treatment group)/%risk in the control group
1-RR (must use decimal form of RR)
59
What does the RR and RRR provide?
The RR and RRR provide relative (proportional) differences in risk between the treatment group and the control group (no meaning in terms of absolute risk)
60
Why is absolute risk reduction more useful than RR and RRR?
Absolute risk reduction is more useful because it includes the reduction in risk and the incidence rate of the outcome
61
What is the ARR formula?
ARR = (% risk in control group) - (% risk in treatment group)
62
What is the additional benefit of calculating the ARR?
An additional benefit of calculating the ARR is to be able to use the inverse of theARR to determine the number needed to treat (NNT) and number needed to harm (NNH)
63
What is number needed to treat (NNT)?
NNT is the number of patients who need to be treated for a certain period of time in order for one patient to benefit
64
What is the NNT formula?
NNT = 1/(risk in control group - risk in treatment group)
NNT = 1/ARR
65
What is number needed to harm (NNH)?
NNH is the number of patients who need to be treated for a certain period of time in order for one patient to experience harm
*NNH is calculated with the same formula as NNT
66
What are the rounding rules for NNT and NNH?
For NNT, anything greater than a whole number, round up to the next whole number (avoids overstating the potential benefit of an intervention). For NNH, anything greater than a whole number, round down to the nearest whole number (avoids understating the potential harm of an intervention
*The absolute value of the ARR is used with NNH
67
What is the definition of odds?
Odds are the probability that an event will occur versus the probability that it will not occur
68
What is the odds ratio and when is it used?
In case control studies, the odds ratio is used to estimate the risk of unfavorable events associated with a treatment or intervention
69
How are case control studies designed?
Case control studies enroll patients who have a clinical outcome or disease that has already occurred. The patient medical charts are reviewed retrospectively to search for possible exposures that increased the risk of the clinical outcome or disease
70
How is the odds ratio used in case control studies?
The odds ratio (OR) is used to calculate the odds of an outcome occurring with an exposure, compared to the odds of the outcome occurring without the exposure
71
What is the OR formula?
OR = (number that have the outcome with exposure x number without the outcome without exposure)/(number without the outcome with exposure x number that have the outcome without the exposure)
72
What is a hazard rate and when is it used?
In a survival analysis, a hazard rate is used. A hazard rate is the rate at which an unfavorable event occurs within a short period of time
73
What is the hazard ratio?
The hazard ratio (HR) is the ratio between the hazard rate in the treatment group and the hazard rate in the control group
74
What is the HR formula?
HR = hazard rate in the treatment group/hazard rate in the control group
75
What does it mean when OR or HR = 1?
The event rate is the same in the treatment and control arms. There is no advantage to treatment
76
What does it mean when OR or HR > 1?
The event rate in the treatment group is higher than the event rate in the control group
77
What does it mean when OR or HR < 1?
The event rate in the treatment group is lower than the event rate in the control group
78
What is a primary endpoint?
The primary endpoint is the main (primary) result that is measured to see if the treatment has a significant benefit
79
What is a composite endpoint?
A composite endpoint combines multiple individual endpoints into one measurement
80
Why are composite endpoints attractive to researchers?
This is attractive to researchers, as combining several endpoints increases the likelihood of reaching a statistically significant benefit with a smaller, less costly trial
*When a composite endpoint is used, each individual endpoint gets counted toward the same (composite) outcome
81
For composite endpoints, what must all the endpoints included have?
All endpoints in a composite must be similar in magnitude and have similar, meaningful importance to the patient
82
What does the FDA require with composite endpoints?
The FDA requires each individual endpoint to be measured and reported when a composite endpoint is used
83
What is a warning associated with composite endpoints?
When assessing a composite measurement, it is important to use the composite endpoint value, rather than adding together the values for the individual endpoints. The value of the sum of the individual endpoints may not equal the value of the composite endpoint, since a patient can have more than one non-fatal endpoint during a trial
84
What methods can be used for continuous data to determine if something is statistically significant?
If it is normally distributed, parametric methods are appropriate. If the data is not normally distributed, nonparametric methods are appropriate
85
What are T-tests?
This is a parametric method used when the endpoint has continuous data and the data is normally distributed
86
When is a one sample t-test performed?
When data from a single sample group is compared with known data from the general population, a one-sample t-test is performed
87
When is a paired t-test used?
If a single sample group is used for a pre-/post- measurement, a paired t-test is appropriate
88
When is a student t-test used?
A student t-test is used when the study has two independent samples: the treatment and the control groups
89
When is analysis of variance (ANOVA) used?
Analysis of variance (ANOVA), or the F-test, is used to test for statistical significance when using continuous data with 3 or more samples, or groups
90
What type of statistical test is used for nominal or ordinal data?
For nominal or ordinal data, a chi-square test is used to determine statistical significance between treatment groups
91
What parametric tests are used for numerical/continuous data that has only one group?
One-sample t-test, dependent/paired t-test (if one group has before and after measures)
92
What parametric test is used with numerical/continuous data that has two groups?
Independent/unpaired student t-test
93
What parametric test is used for numerical/continuous data with three or more groups?
ANOVA (or F-test)
94
What non-parametric test is used for numerical/continuous data with one group?
Sign test, Wilcoxon Signed-Rank test (if one group has before and after measures)
95
What non-parametric test is used for numerical/continuous data with two groups?
Mann-Whitney (Wilcoxon Rank-Sum) test
96
What is a non-parametric test for numerical/continuous data with three or more groups?
Kruskal-Wallis test
97
What are statistical tests for discrete/categorical data with one group?
Chi-square test, Wilcoxon Signed-Rank (if one group has before and after measures)
98
What are statistical tests for discrete/categorical data with two groups?
Chi square test or Fisher's exact test, Mann-Whitney (Wilcoxon Rank-Sum) test (may be preferred for ordinal data)
99
What is a statistical test for discrete/categorical data for three or more groups?
Kruskal-Wallis test
100
What is correlation?
Correlation is a statistical technique that is used to determine if one variable changes, or is related to, another variable
101
When does correlation become positive or negative?
When the independent variable causes the dependent variable to increase, the direction of the correlation is positive (increases to the right). When the independent variable causes the dependent variable to decrease, the direction of the correlation is negative (decreases to the right).
102
What correlation tests are used for ordinal, ranked data?
Spearman's rank-order correlation, referred to as Rho, is used to test correlation with ordinal, ranked data
103
What is the primary correlation test used for continuous data?
The primary test used for continuous data is the Pearson's correlation coefficient, denoted as r, which is calculated score that indicates the strength and direction of the relationship between two variables. The values range from -1 to +1
104
What is something important to not about correlation analysis?
It is not possible to conclude from a correlation analysis that the change in a variable causes the change in another variable. A correlation, whether positive or negative, does not prove a causal relationship
105
What is regression?
Regression is used to describe the relationship between a dependent variable and one or more independent (or explanatory) variables, or how much the value of the dependent variable changes when the independent variable changes
106
Where is regression common to be seen?
Regression is common in observational studies where researchers need to assess multiple independent variables or need to control for many confounding factors
107
What are the three typical types of regression?
Linear (for continuous data), logistic (categorical data), cox regression (for categorical data in a survival analysis)
108
What is sensitivity?
Sensitivity describes how effectively a test identifies patients with the condition
109
What does a higher sensitivity indicate?
The higher the sensitivity, the better; a test with 100% sensitivity will be positive in all patients with the condition
110
How is sensitivity calculated?
Sensitivity is calculated from the number of patients who test positive, out of those who actually have the condition (sensitivity is the percentage of "true positive" results)
111
What is specificity?
Specificity describes how effectively a test identifies patients without the condition
112
What does a high specificity indicate?
The higher the specificity the better; a test with 100% specificity will be negative in all patients without the condition
113
How is specificity calculated?
Specificity is calculated from the number who test negative, out of those who actually do not have the condition (specificity is the percentage of "true-negative" results)
114
What is the sensitivity formula?
Sensitivity = number that have the condition with a positive test result/(number that have the condition with a positive test result + number that have the condition with a negative test result)
115
What is the specificity formula?
Specificity = number without the condition with a negative test result/(number without the condition with a positive test result + number without the condition with a negative test result)
116
What is the intention to treat analysis?
Intention to treat analysis includes data for all patients originally allocated to each treatment group (active and control) even if the patient did not complete the trial according to the study protocol
*Provides a conservative (real-world) estimate of the treatment effect
117
What is a per protocol analysis?
A per protocol analysis is conducted for the subset of the trial population who completed the study according to the protocol (or at least without any major protocol violations)
*Can provide an optimistic estimate of treatment effect since it is limited to the subset of patients who were adherent to the protocol
118
What trials are used to demonstrate that a new drug is roughly equivalent or at least not inferior to the standard of care?
Two types of trials used for this purpose are equivalence and non-inferiority trials
119
What are equivalence trials?
Equivalence trials attempt to demonstrate that the new treatment has roughly the same effect as the old (or reference) treatment
*These trials test for effect in two directions, for higher or lower effectiveness, which is called a two-way margin
120
What are non-inferiority trials?
Non-inferiority trials attempt to demonstrate that the new treatment is no worse than the current standard based on the predefined non-inferiority (delta) margin
121
What is the delta margin?
The delta margin is the minimal difference in effect between two groups that is considered clinically acceptable based on previous research
122
What are forest plots?
Forest plots are graphs that have a "forest" of lines
123
When are forest plots used?
Forest plots can be used for a single study in which individual endpoints are pooled (gathered together) into a composite endpoint. More commonly, forest plots are used when the results from multiple studies are pooled into a single study, such as with a meta-analysis
124
What do forest plots provide?
Forest plots provide CIs for difference data or ratio data
125
What do interpreting forest plots help identify?
Interpreting forest plots correctly can help identify whether a statistically significant benefit has been reached
126
What do the boxes in a forest plot show?
The boxes show the effect estimate. In a meta-analysis, the size of the box correlates with the size of the effect from the single study shown
*Diamonds represent pooled results from multiple studies
127
What do horizontal lines in forest plots show?
The horizontal lines through the boxes illustrate the length of the confidence interval for that particular endpoint (in a single study) or for the particular study (in a meta-analysis)
*The longer the line, the wider the interval, and the less reliable the study results. The width of the diamond in a meta-analysis serves the same purpose
128
What does the vertical line in a forest plot represent?
The vertical solid line is the line of no effect; a significant benefit has been reached when data falls to the left of the line; data to the right of the line indicates significant harm
*The vertical line is set at zero for difference data and one for ratio data
129
What are common types of medical studies?
Case-control studies, cohort studies, randomized controlled trials, meta-analyses
130
What is a case-control study?
Compares patients with a disease (cases) to those without the disease (controls). The outcome of the cases and controls is already known, but the researcher looks back in time (retrospectively) to see if a relationship exists between the disease (outcome) and various risk factors
131
What are the benefits of a case-control study?
Data is easy to get from medical records, good for looking at outcomes when the intervention is unethical, less expensive than a RCT
132
What are the limitations of a case-control study?
Cause and effect cannot reliably be determined (associations may be proven to be non-existent)
133
What is a cohort study?
Compares outcomes of a group of patients exposed and not exposed to a treatment; the researcher follows both groups prospectively or retrospectively (less common) to see if they develop the outcome
134
What is the benefit of cohort studies?
Good for looking at outcomes when the intervention would be unethical
135
What are the limitations of a cohort study?
More time-consuming and expensive than a retrospective study. Can be influenced by cofounders, which are other factors that affect the outcome
136
What is a cross-sectional survey?
Estimates the relationship between variables and outcomes (prevalence) at one particular time (cross-section) in a defined population
137
What is a benefit of a cross-sectional survey?
Can identify associations that need further study (hypothesis-generating)
138
What is a limitation of a cross-sectional survey?
Does not determine causality (further studies needed if association found)
139
What is a case report and case series?
Describes an adverse reaction or a unique condition that appears in a single patient (case report) or a few patients (case series). The outcome of the case in each of these is already known
*A case series is more reliable than a case report
140
What are the benefits of case reports and case series?
Can identify new diseases, drug side effects or potential uses and generates hypotheses that can be tested with other study designs
141
What is a limitation of case reports and case studies?
Conclusions cannot be drawn from a single or few cases
142
What is a randomized controlled trial (RCT)?
Compares an experimental treatment to a control (placebo or existing treatment) to determine which is better. Subjects with the desired characteristics (inclusion criteria) are carefully selected, and patients with characteristics that may influence the outcome are excluded (exclusion criteria). Patients are randomized (have an equal chance of being assigned to the treatment or control group) and sometimes blinded (unaware if they are receiving treatment or control)
143
What is a double blind design?
A double blind design means that both the patient and the investigator are unaware of the treatment assignments for each individual
144
What are the benefits of randomized controlled trial?
Preferred study type to determine cause and effect or superiority, less potential for bias
145
What are the limitations of randomized controlled trials?
Time-consuming and expensive, may not reflect real-life scenarios (when rigorous exclusion criteria are used
146
What is a parallel RCT?
Subjects are randomized to the treatment or control arm for the entire study
147
What is a crossover RCT?
Patients are randomized to one of two sequential treatments. Group 1 receives treatment A first, then crossover to treatment B. Group B receives treatment B then crossover to treatment A
148
What is the benefit of a crossover RCT?
Patients serve as their own control so this minimizes the effects from confounders
149
What is a limitation of a crossover RCT?
A washout period is needed to minimize the influence of the first drug during the second treatment
150
What is a factorial design?
Randomizes to more than the usual two groups to test a number of experimental conditions
151
What is the benefit of a factorial design?
Evaluates multiple interventions (multiple drugs or dosing regimens) in a single experiment
152
What is the limitation of factorial design?
With each arm added, more subjects are needed to have adequate power
153
What is a meta-analysis?
Combines results from multiple studies in order to develop a conclusion that has greater statistical power than is possible from the individual smaller studies
154
What is the benefit of a meta-analysis?
Smaller studies can be pooled instead of performing a large, expensive study
155
What are the limitations of a meta-analysis?
Studies may not be uniform (size, inclusion and exclusion criteria), validity can be compromised if lower quality studies are weighted equally to higher quality studies
156
What is a systematic review article?
Summary of the clinical literature that focuses on a specific topic or question. Begins with a question followed by a literature search, then the information is summarized and sometimes includes a meta-analysis to synthesize results
157
What is the benefit of a systematic review article?
Inexpensive (studies already exist)
158
What is pharmacoeconomics?
Pharmacoeconomics is a collection of descriptive and analytic techniques for evaluating pharmaceutical interventions
159
What is pharmacoeconomic research?
Pharmacoeconomic research identifies, measures and compares the costs (direct, indirect and intangible) and the consequences (clinical, economic and humanistic) of pharmaceutical products and services
160
What are the various research methods used to determine impact of the pharmaceutical product or service?
Cost-effectiveness analysis, cost-minimization analysis, cost-utility analysis and cost-benefit analysis
161
What are pharmacoeconomic methods?
Pharmacoeconomic methods are specific to assessing the costs and consequences of pharmaceutical products and services
162
What is outcomes research?
Outcomes research represents a broader research discipline that attempts to identify, measure and evaluate the end result of healthcare services
163
What do pharmacoeconomic analyses provide?
Pharmacoeconomic analyses provide useful supplemental evidence to traditional efficacy and safety endpoints. They help translate important clinical benefits into economic and patient-centered terms, and can assist providers and payers in determining where, or if, a drug fits into the treatment paradigm for a specific condition
164
What do pharmacoeconomic studies serve to do?
Pharmacoeconomic studies serve to guide optimal healthcare resource allocation in a standardized and evidence-based manner
165
What does the ECHO model stand for and what does it provide?
The ECHO model (Economic, Clinical and Humanistic Outcomes) provides a broad evaluative framework to assess the outcomes associated with diseases and treatments
166
What are economic outcomes?
Include direct, indirect and intangible costs of the drug compared to a medical intervention
167
What are clinical outcomes?
Include medical events that occur as a result of the treatment or intervention
168
What are humanistic outcomes?
Include consequences of the disease or treatment as reported by the patient or caregiver
169
What are examples of direct medical costs?
Drug preparation and administration (including home infusion supplies), inpatient direct costs (hospital bed, administration, medical staff, surgeries, procedures, labs), outpatient direct costs (office and clinic visits)
170
What are example of direct non-medical costs?
Travel and lodging costs for patients and caregivers traveling to the hospital or clinic, household costs such as childcare or eldercare, home health aides, to help with dressing/bathing and other activities
171
What are examples of indirect costs?
Lost work time, lost work productivity, morbidity (costs from having the disease and related disability), mortality (death)
172
What are examples of intangible costs?
Pain, suffering, anxiety, fatigue
173
What are average cost-effectiveness ratios?
Average cost-effectiveness ratios reflect the cost per outcome of one treatment independent of other treatment alternatives
174
What are incremental cost-effectiveness ratios?
Incremental cost-effectiveness ratios represent the change in costs and outcomes when two treatment alternatives are compared. An incremental cost-effectiveness ratio is calculated when evaluating costs and outcomes between competing alternatives, and represents the additional costs required to produce an additional unit of effect
175
How do you calculate incremental cost ratio
(C2-C1)/(E2-E1) where C is for costs and E is for effects
176
What is cost minimization analysis?
Cost minimization analysis (CMA) is used when two or more interventions have demonstrated equivalence in outcomes, and the costs of each intervention are being compared
177
What does CMA compare?
CMA measures and compares the input costs of treatment alternatives that have equivalent outcomes
178
What is the benefit and limitation of CMA?
CMA is considered the easiest analysis to perform, but use of this method is limited given its ability to compare only alternatives with demonstrated equivalent outcomes
179
What is a cost-benefit analysis (CBA)?
Cost-benefit analysis (CBA) is a systematic process for calculating and comparing benefits and costs of an intervention in terms of monetary units (dollars)
180
What does a CBA consist of?
CBA consists of identifying all the benefits from an intervention and converting them into dollars in the year that they will occur. The costs associated with the intervention are identified, allocated to the year when they occur and then discounted back to their present day value/ Given that all other factors remain constant, the program with the largest present day value of benefits minus costs is the best economic value
181
What are the limitations and benefits of CBA?
In CBA, it can be difficult to assign a dollar amount to a benefit. One advantage to using CBA is the ability to determine if the benefits of the intervention exceed the costs of implementation. CBA can also be used to compare multiple programs for similar or unrelated outcomes, as long as the outcome measures can be converted to dollars.
182
What is a cost-effectiveness analysis (CEA)?
Cost-effectiveness analysis (CEA) is used to compare the clinical effects of two or more interventions to respective costs. The resources associated with the intervention are usually measured in dollars, and clinical outcomes are usually measured in natural health units.
183
What are the advantages of CEA?
The main advantage of this method is that the outcomes are easier to quantify when compared to the other analyses, and clinicians are familiar with these types of outcomes since they are similar to outcomes seen in clinical trials and practice. CEA is the most common pharmacoeconomic methodology seen in biomedical literature
184
What are disadvantages of CEA?
A disadvantage of CEA is the inability to directly compare different types of outcomes. It is also difficult to combine two or more outcomes into one value of measurement
185
What is a cost-utility analysis (CUA)?
Cost-utility analysis (CUA) is a specialized form of CEA that includes a quality of life component of morbidity assessments, using common health indices such as quality-adjusted life years (QALY) and disability-adjusted life years (DALYs)
186
What does CUA measure?
In CUA, the intervention outcome is measured in terms of QALYs gained. CUA measures outcomes based on years of life that are adjusted by utility weights, which range from 1 for "perfect health" to 0 for "dead"
*QALY takes into account both the quality (morbidity) and the quantity (mortality) of life gained
187
What is an advantage of CUA?
An advantage of CUA is that different types of outcomes and diseases with multiple outcomes of interest, can be compared
188
What is health related quality of life (HRQOL)?
Health related quality of life (HRQOL) refers to the effects of a disease and its treatment on an individual's function and well-being, as perceived by the individual
189
What does HRQOL comprise of?
HRQOL is comprised of several important domains, including physical and mental functioning, role functioning, vitality, social functioning and general health perceptions
190
What do HRQOL assessments provide?
HRQOL assessments can provide important patient-centered information related to the effects of a disease or treatment on patient functioning and well-being. These assessments are typically developed as either general health status instruments that can be used across a number of disease areas or disease-specific measures applicable to a limited disease population
