POP health/Epi/Ethics/CANMEDS Flashcards
5 components to a research consent document
1) Invitation to participate
2) Provides name of PI and RA; describes study in question including study procedures, duration of participation, participant responsibilities
3) Written in a grade 5 comprehension level
4) Describes risks, benefits (If no direct benefit is anticipated, that should be stated.
5) Provides option to withdraw consent at any time
6) Disclosure of conflicts of interest from investigators/sponsors/institutions
7) Signature of RA and patient with date
3 components to informed consent
1) Disclosure (disclosing information needed to make a decision)
2) Capacity (competency of the patient)
Patient must be able to communicate their treatment choice
Express understanding
Appreciation of the illness, treatment options, and likely outcomes that will affect them
Rationalize the risks/benefits
3)Voluntariness (voluntary nature of the decision)
6 components to informed consent
1) Disclosure – must supply the subject with the information necessary to make
autonomous decision (must describe risks and benefits and other treatment alternatives)
2) Comprehension – subjects have adequate comprehension of the information provided (written in clear, understandable language)
3) Capacity – pertains to the ability of the subject to both understand the information provided and form a reasonable judgment based on the potential consequences of his decision
4) Voluntariness – refers to the subjects’ rights to freely exercise his/her decision making without being subjected to external pressure such as manipulation or influence
5) Must describe consequence of not treating (part of disclosure)
6) Awareness of treatment alternatives
What to do if someone declines informed consent
1) assess capacity
2) document decision
When looking at epidemiological data, what are 3 ways to control for confounders
Propensity matching
Multivariate analysis
Stratification
Age-standardized incidence for cancer rates - why do we do it? How is it done?
We do it because it all allows for a more representative comparison of two different populations (across time or across geographical regions)
It is done by calculating incidence of cancer rate per age grouping (ie. 10 cases per 100,000 aged 1-40yo, then multiplying that number by the proportion of the entire population composed of that age group. i.e. 10 multipy by 0.6 (if 60% of population 1-40yo) + (x multiply by 0.4 (if rest of population is one group).
What is Type I, Type II error, P value, Power
type I error = probability of rejecting the null hypothesis when it is true (Type 1 error = alpha)
type II error = probability of failing to reject the null hypothesis when it is false (Type 2 error = beta)
Power = The probability of making a correct decision (to reject the null hypothesis) when the null hypothesis is false (1-Beta).
P value: the probability under the assumption of no effect or no difference (null hypothesis) of obtaining a result equal to or more extreme than what was actually observed
The statistical association between a supposed risk factor and a disease state does not necessarily mean that a specific risk factor causes the disease. List 4 criteria suggesting that a given exposure may cause a disease, rather than just being mathematically associated with the disease (Bradford hill criteria)
- Strength of the statistical association
- Adequate time sequence (exposure precedes disease, enough time to develop disease after exposure)
- Biologic plausibility (does it make sense scientifically)
- Dose response relationship
- Consistency with other investigation
- Specificity (does altering only the cause alter the effect or are there multiple other factors)
8 Modifiable breast cancer risk factors
Parity (less risk if more babies)
Time of first pregnancy
Breastfeeding duration
Weight loss
Use of oral contraceptive pill
Use of hormone replacement therapy
Use of selective estrogen receptor modulator (raloxifene)
Choice to have prophylactic oophorectomies
Choice to have prophylactic mastectomies
Alcohol
Physical activity
Smoking
What do you need to calculate positive predictive value:
prevalence, sensitivity, prevalence
Define intention to treat analysis
Analysis based on the initial treatment assignment (i.e., intended treatment), not on the treatment actually received.
Define intention to treat analysis. Beside bias, why is it important?
Analysis based on the initial treatment assignment (i.e., intended treatment), not on the treatment actually received.
- Important to preserve randomization
- ** IIT is more reflective of real life (because in real life there will also be patients who do not complete the treatment!)
Three factors to determine sample size
Power of study (P= 1- beta)
Level of significance (alpha; usually 0.05)
Expected effect size
Underlying rate in the population
Standard deviation in the population
What tests to compare kaplan meier curves
Log rank test
Cox proportion hazard test
Define and give formula:
Sensitivity
Specificity
PPV
NPV
Sensitivity = probability that negative test rules out disease (true positives) = True positives / all diseased
Specificity = probability that positive test rules in disease (true negatives) =True negatives / all non-diseased
PPV = probability have the disease if the test is positive; low prevalence gives high FP rate so PPV increases with increasing prevalence
= True positives / all positives
NPV means probability of negative test not having disease; decreases with increasing prevalence
= True negatives / all negatives
