Behavioral Science-biostatistics/epidemiology/ethics/development And Aging

1. The upper limit of normal of the fasting blood glucose for diagnosing diabetes mellitus has been lowered from 140 mg/dL to 126 mg/dL. What effect does this change have on diagnosing diabetes mellitus?

Has no impact on diagnosing diabetes mellitus

Increases the likelihood of false negative results in diagnosing diabetes mellitus

*Increases the predictive value of a negative test result(Increases NPV), as we made the test more sensitive you will have less FN (You cantch more people with disease)and more TN(you also increased number of FP so PPV and specificity go down)*formula for calculating the NPVis TN/TN + FN. Tests with 100% sensitivity always have a 100% NPV; therefore, a negative test result excludes disease.The less the FP rate, the greater the specificity of a test. A test with no FPs has 100% specificity. The predictive value of a positive test result (PV+) is the likelihood that a positive test result is a TP rather than a FP; therefore, the formula for PPV is TP/TP + FP. Tests with 100% specificity always have a PV+ of 100%; therefore, they are most useful for confirming disease.

Decreases the accuracy of diagnosing diabetes mellitus

By lowering the upper limit of normal for fasting blood glucose, we are making the test more sensitive to detect diabetes mellitus cases. As a result, the predictive value of a negative test result (NPV) increases, meaning there will be fewer false negative results. This adjustment increases the number of true negatives and true positives, but also increases false positives, leading to a decrease in positive predictive value (PPV) and specificity.
Since a negative test result excludes disease, a higher NPV is desired for accurate diagnosis. The change does not decrease the accuracy of diagnosing diabetes or increase false negatives; rather, it improves the ability to rule out the presence of the disease.

Explanation

By lowering the upper limit of normal for fasting blood glucose, we are making the test more sensitive to detect diabetes mellitus cases. As a result, the predictive value of a negative test result (NPV) increases, meaning there will be fewer false negative results. This adjustment increases the number of true negatives and true positives, but also increases false positives, leading to a decrease in positive predictive value (PPV) and specificity.
Since a negative test result excludes disease, a higher NPV is desired for accurate diagnosis. The change does not decrease the accuracy of diagnosing diabetes or increase false negatives; rather, it improves the ability to rule out the presence of the disease.

2. What type of study is designed to evaluate the feasibility of treatment X in children with chronic headaches and is susceptible to selection bias?

Cross-Sectional Study

*This type of PROSPECTIVE Study is called CASE SERIES-Note that in this medical research you track group of people with similar exposure(here Treatment X) to establish correlation between exposure and outcome, HOWEVER note that it Has No Control-group(Hence has Low Internal Validity>As you selectively pick particular group based on their exposure, Case series studies are especially susceptible to SELECTION Bias.*AT LEAST you should know that case series/case report studies are type of DESCRIPTIONAL studies at the levels of Individuals/small groups and that one of the example of case report studies was study of Young individual males with PCP that eventually lead to discovery of AIDS.If you don't get anything here remember to do this on examp: Ask yourself does the study compare AT LEAST 2 DIFFERENT groups(Or more)? if the answer is NO then you can pick case series/case reports(These 2 are kinda same case series basically will pick Men who use IV drugs as a single group and report it, while case reports will report them individually, point is you do NOT compare them to people who are Not IV drug users, you just check what is going on in those cases).

Randomized Controlled Trial

Case-Control Study

In this case, the study is tracking a group of children with chronic headaches receiving treatment X, without comparing them to another group. Therefore, it falls into the category of a case series study.

Explanation

In this case, the study is tracking a group of children with chronic headaches receiving treatment X, without comparing them to another group. Therefore, it falls into the category of a case series study.

3. You organize subjects into smokers and nonsmokers and note who gets COPD. Uncontrolled hypercholesterolemia and Controlled, you note who gets MI. What type of study is this and what information does it provide?

Cross-sectional study (you look at a snapshot in time to see the association between exposures and outcomes)

Retrospective Case-Control study (you compare individuals with the disease to those without looking back to see what exposures they had)

Experimental study (you intervene by assigning subjects to different exposures and measure the outcomes)

*Prospective Cohort study(you want to know who will get the disease), if you divided participants into exposed vs non-exposed group but checked who has already developed the disease than it would've been "Historical" Cohort study.(Like check who developed cancer:Radiologists vs Other physicians, exposure was radiation)In other words Cohort study gives you information about Relative Risk(RR)=Probability of event occurring in exposed/Probability of event occurring in Non-exposed group-Basically tells your HOW MUCH MORE likely those who were exposed to Risk will develop/developed the disease.

A prospective cohort study is the most appropriate for this scenario as it allows researchers to follow participants over time to observe the development of diseases based on their exposures. Retrospective case-control studies, cross-sectional studies, and experimental studies have different designs and objectives that do not match the requirements of this question.

Explanation

A prospective cohort study is the most appropriate for this scenario as it allows researchers to follow participants over time to observe the development of diseases based on their exposures. Retrospective case-control studies, cross-sectional studies, and experimental studies have different designs and objectives that do not match the requirements of this question.

4. Your group went out in streets and asked people 2 questions: 1) Do you eat Junk food? 2) Do you have Abdominal pain? What type of study does this resemble? Can you say that Junk food Causes Abdominal pain?

A. Longitudinal study

B. Randomized controlled trial

C. Cohort study

*You basically assessed what happens at this moment not years after or before the start of study but right now how many people who eat junk food also complain of abdominal pain?That Best fits Cross-sectional study description...even if all 100 out of 100 who ate junk food also complained of abdominal pain you ABSOLUTELY Can NOT say that Junk food causes abdominal pain(Just as you can't say that abdominal pain leads to people eating junk food, it can be either one of these 2statements), all you can say is that there is a CORRELATION between these 2 but you can NOT establish Causality<Highly tested characteristic of cross-sectional study.

In this scenario, the study resembles a Cross-sectional study, as it looks at the relationship between junk food consumption and abdominal pain at a single point in time. It is important to note that finding a correlation does not imply causation. Therefore, it would be incorrect to conclude that junk food causes abdominal pain based on this study.

Explanation

In this scenario, the study resembles a Cross-sectional study, as it looks at the relationship between junk food consumption and abdominal pain at a single point in time. It is important to note that finding a correlation does not imply causation. Therefore, it would be incorrect to conclude that junk food causes abdominal pain based on this study.

5. If the alpha is set at 0.01 instead of 0.05, what will happen to the likelihood of making a type 1 error?

The likelihood of making a type 1 error will increase

The likelihood of making a type 1 error will decrease

The likelihood of making a type 1 error will stay the same

*Type 1 error-is basically false positives(Stating that there is an effect or difference when none exists=null hypothesis incorrectly rejected in favor of alternative hypothesis), and P-value corresponds to this chance(alpha), obv. lower the value(P<0.01 instead of 0.05) the higher is your confidence in reporting the significant findings.

Setting alpha at a lower value (0.01 instead of 0.05) actually decreases the likelihood of making a type 1 error, as it increases the confidence in the statistical significance of findings.

Explanation

Setting alpha at a lower value (0.01 instead of 0.05) actually decreases the likelihood of making a type 1 error, as it increases the confidence in the statistical significance of findings.

6. A test is performed on 5 normal people who have the following test results: 49 mg/dL, 54 mg/dL, 51 mg/dL, 56 mg/dL, and 60 mg/dL. The standard deviation of the test is 4 mg/dL. What is the reference interval (normal range) for the test?

48-58

*First find Mean=49+51+54+56+60=260/5=52.*Normal range is +-2SD, hence 52-4x2=44,52+4x2=60.<So normal range here is 44-60

40-65

55-58

First find Mean=49+51+54+56+60=260/5=52. Normal range is +-2SD, hence 52-4x2=44, 52+4x2=60. So normal range here is 44-60.

Explanation

First find Mean=49+51+54+56+60=260/5=52. Normal range is +-2SD, hence 52-4x2=44, 52+4x2=60. So normal range here is 44-60.

7. What do you need to evaluate in order to determine sensitivity when evaluating a new blood test to detect prostate cancer?

Prostate biopsies of men with test results exceeding 5 ng/mL.

*Prostate biopsies of men with test results equal to or below 5 ng/mL.(To evaluate False Negatives)*Remember sensitivity equals TP/TP+FN, we know TP (90), so now we need to find out FN(So on test <5 means that they are negative, but if biopsy shows that they indeed have cancer=False negative)

Testing the efficacy of the blood test in detecting other types of cancer.

Biopsies of men with no PSA testing done.

In order to determine sensitivity, false negatives need to be evaluated by conducting prostate biopsies on men with test results equal to or below 5 ng/mL to see if they actually have prostate cancer. This helps in calculating the true positive (TP) and false negative (FN) values required for the sensitivity calculation.

Explanation

In order to determine sensitivity, false negatives need to be evaluated by conducting prostate biopsies on men with test results equal to or below 5 ng/mL to see if they actually have prostate cancer. This helps in calculating the true positive (TP) and false negative (FN) values required for the sensitivity calculation.

8. If a scientist steals the 7th result of an experiment from the sequence 1,2,3,4,5,6,7, how would the Median, Mean, and Mode change?

Mean would change to 5, Median would change to 4, and Mode would change to 3.

*Well first Mean was 1+2+3+4+5+6+7/7=(4), now mean is 1+2+3+4+5+6/6=3.5*Median was 4 (just pick the number in middle of first line), Median for second case would be mean of middle 2 as you can't pick 1 middle number, so here it would be 3,5.*Mode won't be affected here as it is simply the value that occurs most often in data(So for example in our cases if 3 for example was repeated 2 times-more than any other number, it would be the mode, so even in that case mode wouldn't be changed as still the most repeated value is 3).*So in the end Mean and Median would decrease however Mode won't change.

Mean would change to 4, Median would change to 4, and Mode would change to 4.

Mean would change to 3.5, Median would change to 2.5, and Mode would change to 1.

The correct mean is calculated by finding the sum of all the numbers divided by the count. In this case, the mean would decrease from 4 to 3.5 when the 7 is removed. The median, which is the middle number, would also change from 4 to 3.5 since the two middle numbers (3 and 4) would be averaged. The mode, which is the most frequently occurring number, would remain the same as the number 3 still occurs the most in the dataset.

Explanation

The correct mean is calculated by finding the sum of all the numbers divided by the count. In this case, the mean would decrease from 4 to 3.5 when the 7 is removed. The median, which is the middle number, would also change from 4 to 3.5 since the two middle numbers (3 and 4) would be averaged. The mode, which is the most frequently occurring number, would remain the same as the number 3 still occurs the most in the dataset.

9. From 1000 patients who receive placebo, 30 of them die. From another 1000 patients who receive drug X, 20 people die. These observations are made over 3 years. If the drug cost per patient is 500 bucks per year, how much money should be spent to save 1 patient?

*Basically drug saves 10 more people when compared to placebo.*So to save 1 guy yo need to treat at least 100 guys.*That means you have to spend 100 x500=50000*And that over 3 years.*50000x3=150000.Pretty important card believe me.

To save 1 patient, 200 patients need to be treated. Therefore, the total cost to save 1 patient over 3 years would be 300,000 bucks.

To save 1 patient, 25 patients need to be treated. Therefore, the total cost to save 1 patient over 3 years would be 100,000 bucks.

To save 1 patient, 50 patients need to be treated. Therefore, the total cost to save 1 patient over 3 years would be 75,000 bucks.

The correct calculation is based on the fact that the drug saves 10 more people compared to the placebo, leading to a total of 100 patients needing to be treated to save 1 life over 3 years.

Explanation

The correct calculation is based on the fact that the drug saves 10 more people compared to the placebo, leading to a total of 100 patients needing to be treated to save 1 life over 3 years.

10. Study is conducted to assess the activity of a new drug in patients with disease X. All patients enrolled in the study are informed that they would be treated with the drug X, they are assigned to successive dose cohorts of 400 to 1000 mg/day of the drug. Researches monitor the results of the groups (Divided by doses they get). This study is best described as?

Single-blind Clinical Trial - only the researches know who receives what treatment, participants are unaware.

Double-blind Clinical Trial - neither the researchers nor the participants know who receives what treatment until the study is completed.

*Open-labeled Clinical trial-this is the trial when BOTH researchers but also participants know who receives what treatment.*So here both researchers and the participants know that they get drug X.

Placebo-controlled Clinical Trial - some participants receive a placebo instead of the drug, while others get the actual drug being tested.

11. Particular disease is more common in dizygotic twins than in monozygotic twins. What does that tell you about environmental vs genetic influence on that disease?

The disease is purely genetic in nature

*That Environmental influence plays greater role, remember ONLY MONOzygotic twins are IDENTICAL genetically.<This is Twin concordance study.Don't confuse with adoption study-where Siblings are raised in different families(Can be biological vs Adopted family), but that study too can give you idea about genetic/environmental influences on trait/disease.

Dizygotic twins share more genetic similarities compared to monozygotic twins

Monozygotic twins have a higher chance of developing the disease

In this case, the fact that the disease is more common in dizygotic twins than in monozygotic twins suggests that environmental influences play a greater role in the development of the disease. This is because only monozygotic twins are genetically identical, so differences in disease prevalence between the two types of twins point more towards environmental factors.

Explanation

In this case, the fact that the disease is more common in dizygotic twins than in monozygotic twins suggests that environmental influences play a greater role in the development of the disease. This is because only monozygotic twins are genetically identical, so differences in disease prevalence between the two types of twins point more towards environmental factors.

12. What is a Phase 0 clinical trial?

Phase 0 trials involve testing the drug on a large population to see its effectiveness and toxicity.

*Micro-dosing studies-when around 10-15 people receive Lower than normal doses of drugs, just receive information about PharmacoKinetics(What your body does to drug) and Pharmacodynemics(what drug does to you,mechanism of action),subtherapeutic doses(used in phase0) won't let you know how effective/toxic is this drug.

Phase 0 trials determine the optimal dosage of the drug for future studies.

Phase 0 trials focus on comparing the drug with existing treatments in the market.

Phase 0 clinical trials, also known as micro-dosing studies, involve administration of subtherapeutic doses to a small number of participants to primarily gather pharmacokinetic and pharmacodynamic data.

Explanation

Phase 0 clinical trials, also known as micro-dosing studies, involve administration of subtherapeutic doses to a small number of participants to primarily gather pharmacokinetic and pharmacodynamic data.

13. What type of study determines the PREVALENCE of Heart disease in 2017?

*Cross-sectional study determines prevalence of disease at particular time.(Proportion of people who have disease at that particular point of time)

Longitudinal study determines prevalence of disease over a period of time.

Qualitative study determines the psychological impact of heart disease.

Experimental study determines the causation of heart disease.

A cross-sectional study is used to determine the prevalence of a disease at a specific point in time, while longitudinal studies track the same group of individuals over a longer period to study changes. Experimental studies focus on determining causation, while qualitative studies delve into the psychological aspects.

Explanation

A cross-sectional study is used to determine the prevalence of a disease at a specific point in time, while longitudinal studies track the same group of individuals over a longer period to study changes. Experimental studies focus on determining causation, while qualitative studies delve into the psychological aspects.

14. A study divides patients into 2 groups, one receiving doxorubicin and the other receiving a placebo, to compare the risk of developing dilated cardiomyopathy over the next few months. What type of study design is most appropriate for this scenario?

Case-control study, to determine the causal relationship between doxorubicin use and dilated cardiomyopathy.

Cross-sectional study, to assess the prevalence of dilated cardiomyopathy in patients receiving doxorubicin compared to those receiving a placebo.

*Cohort PROSPECTIVE study, you want to check RR(How much more Likely were the patients on doxorubicin to develop Dilated cardiomyopathy over those who didn't receive that drug)

Randomized controlled trial (RCT), to evaluate the efficacy of doxorubicin in preventing dilated cardiomyopathy in patients.

In this scenario, a cohort prospective study is most appropriate to compare the risk of developing dilated cardiomyopathy in patients receiving doxorubicin versus placebo over time. This design allows for the calculation of relative risk (RR) to measure how much more likely patients on doxorubicin are to develop dilated cardiomyopathy compared to those on placebo.

Explanation

In this scenario, a cohort prospective study is most appropriate to compare the risk of developing dilated cardiomyopathy in patients receiving doxorubicin versus placebo over time. This design allows for the calculation of relative risk (RR) to measure how much more likely patients on doxorubicin are to develop dilated cardiomyopathy compared to those on placebo.

15. What type of study is used for comparison of treatments with each-other/placebo? Specifically in which phase? What can we do to ensure proper quality of the study? At which stage can a drug get FDA approval?

Case Study in Phase I, ensure proper quality by letting patients choose their treatment, FDA approval in Phase II

Experimental Study in Phase II, ensure proper quality by conducting open-label studies, FDA approval in Phase III

Observational Study in Phase IV, ensure proper quality by allowing doctors to select treatment, FDA approval in Phase I

*Clinical Trial involves only humans and best fits description, study should be controlled,Double-blinded(Neither Doctors nor patients know the treatment),randomized.(We minimize Selection,procedure,observer-expectancy bias)Phase III is usually when we compare different treatments with each-other or with placebo, phase III is when drug usually gets FDA approval.

16. What is the primary purpose of a phase I clinical trial?

*Most important thing to remember here is that HEALTHY volunteers(but small number) are entering this phase, here you don' evaluate efficiacy you just want to gain information about Pharmacokinetics(how drug is metabolized),pharmacodynamics(What drug does to body),assess toxicity and thus safety.

To test the drug on individuals with the targeted disease or condition.

To assess the efficacy of the drug in a large population of patients.

To compare the new drug with existing treatments for a specific condition.

17. In which phase of a clinical trial do you want to gain information about efficacy, optimal dosing, and adverse effects?

Phase 1

*Phase 2 phase best fits the description.<Here u answer"Does it work?"<Usually few(Couple of hundred patients with particular Disease participate)

Phase 4

Phase 3

Phase 2 of a clinical trial is where researchers aim to determine if the drug or treatment is effective, the optimal dosing, and any potential adverse effects. Phase 1 focuses on safety, Phase 3 compares the new treatment to existing ones, and Phase 4 involves post-market surveillance.

Explanation

Phase 2 of a clinical trial is where researchers aim to determine if the drug or treatment is effective, the optimal dosing, and any potential adverse effects. Phase 1 focuses on safety, Phase 3 compares the new treatment to existing ones, and Phase 4 involves post-market surveillance.

18. What is the term for the phase of clinical trial that involves post-marketing surveillance of a drug that was approved by the FDA but later found to have rare but debilitating effects?

*Phase IV clinical trial(Post-marketing surveillance)

Phase I clinical trial (Safety testing)

Phase II clinical trial (Efficacy testing)

Phase III clinical trial (Comparative effectiveness)

Phase IV clinical trials are conducted after a drug is approved and on the market to monitor long-term safety and efficacy in a larger population. This phase involves post-marketing surveillance to identify any rare but serious adverse effects that may not have been evident during earlier phases of clinical trials.

Explanation

Phase IV clinical trials are conducted after a drug is approved and on the market to monitor long-term safety and efficacy in a larger population. This phase involves post-marketing surveillance to identify any rare but serious adverse effects that may not have been evident during earlier phases of clinical trials.

19. What is the difference between double blinded and triple blinded studies?

Patients and doctor don't know who receives what...vsEven Researchers don't know who receives what....

Only researchers know who receives what in double blinded studies

Patients know who receives what in double blinded studies

Triple blinded studies involve triple the amount of participants in the study

Double blinded studies involve patients and doctors being unaware of the treatment allocation, while triple blinded studies take it a step further by also keeping the researchers unaware of the treatment allocation.

Explanation

Double blinded studies involve patients and doctors being unaware of the treatment allocation, while triple blinded studies take it a step further by also keeping the researchers unaware of the treatment allocation.

20. 90 out of 100 patients get +result for ELISA(100% sensitivity), how many out of these 10 will NOT have HIV.Can there be more of patients who do NOT have HIV?What you do next in those who have + result?

10 out of 100 patients will NOT have HIV.

*Well as sensitivity is 100%, then the False Negative result is IMPOSSIBLE, all of those who tested negative(10 people) truly do NOT have HIV(False Negative=0).*BUT note that out of those 90 who tested +, some of them can be FALSE positives(So Could be HIV free),because even though ELISA is HIGHLY sensitive test for HIV(Making it a great SCREENING test to rule OUT the disease), it does have some False Positives so for Confirming the result(Ruling in the diagnosis)you need More SPECIFIC test(Less False Positives), so in our case to confirm the diagnosis we would use Western Blot(So yea out of these 90 patients some of them could be HIV free and Ruled OUT by Confirmatory Western blot test).Easiest way to keep them straight is to remember that Highly sensitive test has High rate of True POSITIVE(Catches big proportiono of those who have the disease, mathematically TP/TP+FN=1-FN),while Highly specific test has high rate of True NEGATIVES(Marks negative big proportion of people who do Not have the disease,mathematically TN/TN+FP)

ELISA is a highly specific test for HIV detection.

There can be more patients who do NOT have HIV than those who actually have it.

21. In Some med schools, there are More assholes then in others, if being an Asshole was a disease with More Prevalence in particular med school, how would this change Sensitivity, Specificity, PPV and NPV of 'Asshole test'?

Higher prevalence will decrease PPV and NPV of the 'Asshole test' due to the increased number of false positives.

The prevalence of Assholes in a particular med school will not have any impact on the diagnostic accuracy of the 'Asshole test'.

*Well High prevalence(Number with disease/number of people in that polulation)means that Particular disease is More common in this particular group, so this affects PPV and NPV but with NO effect on Sensitivity,Specificity(Fixed variables)higher prevalence(Higher baseline risk) PPV(Probability that you truly have the disease if you have+result) increases while NPV(Probability that you don't have disease if you have Negative result) decreases.*NOTE VERY IMPORTANT:Even though Sensitivity of test does NOT vary with Prevalence, in population of LOW prevalence of the disease you obviously want more Sensitive test to minimize false Negatives.

If Asshole test is not specific to med school contexts, it's sensitivity and specificity will be significantly impacted by the prevalence of Assholes in the general population.

The correct answer explains how high prevalence affects PPV and NPV without impacting Sensitivity and Specificity. The incorrect answers provide misconceptions about how prevalence may affect the diagnostic accuracy of the 'Asshole test'.

Explanation

The correct answer explains how high prevalence affects PPV and NPV without impacting Sensitivity and Specificity. The incorrect answers provide misconceptions about how prevalence may affect the diagnostic accuracy of the 'Asshole test'.

22. 100 people with no disease are tested. 50 of them test negative. What is the probability of getting at least 1 positive result with this test in 3 patients without the disease?

50% chance of getting at least one False Positive (FP) result.

75% chance of getting at least one False Positive (FP) result.

*well we know that TN value of the test is 50 and we know that FP was 50, we can calculate specificity=TN/TN+FP=50/100=0.5Now probability that all of these 3 patients get True negative would be 0.5 in 3rd degree=(remember specificity gives information about True negatives), but so they basically ask what is probability that NOT all 3 of the tests are true negative(At least 1 is False positive),that would be simply 1-0.125=-0.875.(So there is 87 % chance that you will get at least one FP).it's pretty tough if you didn't study in 3rd grade but still worth of it believe me :P

25% chance of getting at least one False Positive (FP) result.

The probability of at least one False Positive (FP) result can be calculated by finding the complement of the probability that all 3 patients test True Negative (TN). Since the specificity of the test is 0.5 and the probability of all three patients being TN is 0.5^3 = 0.125, the probability of at least one FP result is 1 - 0.125 = 0.875 or 87%.

Explanation

The probability of at least one False Positive (FP) result can be calculated by finding the complement of the probability that all 3 patients test True Negative (TN). Since the specificity of the test is 0.5 and the probability of all three patients being TN is 0.5^3 = 0.125, the probability of at least one FP result is 1 - 0.125 = 0.875 or 87%.

23. You can calculate FP vs FN if you know Specificity vs Sensitivity.....how exactly?

*FP=1-Specificity(Remember Specificity=1-FP).*FN=1-Sensitivity(Remember Sensitivity=1-FN)remember Positive people are SPECial while Negative people are too damn sensitive....<Lame but helps ;)

A. *FP=Specificity(Remember Specificity=FP).*FN=Sensitivity(Remember Sensitivity=FN)

B. *FP=Sensitivity(Remember Sensitivity=FP).*FN=Specificity(Remember Specificity=FN)

C. *FP=Specificity(Remember Specificity=FN).*FN=1-Sensitivity(Remember Sensitivity=FN)

When calculating False Positives (FP) and False Negatives (FN) based on Specificity and Sensitivity, it is important to remember that Specificity is equal to 1 minus FP, and Sensitivity is equal to 1 minus FN. This understanding allows for accurate calculations and ensures the correct interpretation of results in medical or statistical scenarios.

Explanation

When calculating False Positives (FP) and False Negatives (FN) based on Specificity and Sensitivity, it is important to remember that Specificity is equal to 1 minus FP, and Sensitivity is equal to 1 minus FN. This understanding allows for accurate calculations and ensures the correct interpretation of results in medical or statistical scenarios.

24. What can you say about Sensitivity of a test that has 100% NPV and what can you say about Specificity of test that has 100% PPV?

*100% NPV means that NPV(TN/TN+FN)=1, that means that FN is 0, remember sensitivity=(TP/TP+FN) so obviously sensitivity is 1(100%) too.*100% PPV means that FP=0(Remember PPV=TP/TP+FP), if FP is 0 than TN/TN+FP=1(100%), thus if PPV is 100% then Specificity of the test is 100% too.

100% NPV means that Sensitivity is 100% but 100% PPV means that Specificity is 0%

100% NPV means that Sensitivity is 0% but 100% PPV means that Specificity is 100%

100% NPV means that Sensitivity is 0% and 100% PPV means that Specificity is 0%

25. In country A this disease is more common than in country B, if you get a Negative result for that disease in country A, are you more or less likely to really have the disease?

Prevalence of the disease in country A compared to country B has no effect on test results.

*You are MORE likely to have the disease as NPV DECREASES with Increased prevalence.

Getting a Negative result in country A has no impact on likelihood of having the disease.

You are less likely to have the disease as NPV INCREASES with Increased prevalence.

The correct answer is that you are more likely to have the disease as NPV decreases with increased prevalence. This means that in a country where the disease is more common, getting a negative result does not rule out the presence of the disease as effectively as in a country where the disease is less common.

Explanation

The correct answer is that you are more likely to have the disease as NPV decreases with increased prevalence. This means that in a country where the disease is more common, getting a negative result does not rule out the presence of the disease as effectively as in a country where the disease is less common.

26. What does a low threshold for a highly sensitive test result in?

No effect on false positives or false negatives

*LOW threshold,(So on curve it will be shifted to left on your side) so you are MORE likely to have False positives, you traded this to get detect More people with actual disease(Thus to decrease number of False negatives),as you Increase the threshold(Move to the right side), you allow less false positives(Thus you Increase Specificity) however you also Increase False negatives(Thus you Decrease sensitivity)

More false negatives and fewer false positives

Decreased sensitivity and increased specificity

A low threshold for a highly sensitive test trades off more false positives in order to detect more true positives, resulting in fewer false negatives.

Explanation

A low threshold for a highly sensitive test trades off more false positives in order to detect more true positives, resulting in fewer false negatives.

27. What is the term used to describe the probability of a test being negative when you don't have the disease versus the probability of a test being positive when you do have the disease?

*Specificity.vs*Sensitivity

True Positive Rate vs True Negative Rate

Accuracy vs Precision

Reliability vs Validity

Specificity and sensitivity are terms used in medical testing to describe the accuracy of a test in identifying true negatives and true positives, respectively. Specificity refers to the probability of a test correctly identifying those without the disease (true negatives), while sensitivity refers to the probability of a test correctly identifying those with the disease (true positives). Accuracy vs Precision, Reliability vs Validity, True Positive Rate vs True Negative Rate are not the correct terms used to describe this scenario.

Explanation

Specificity and sensitivity are terms used in medical testing to describe the accuracy of a test in identifying true negatives and true positives, respectively. Specificity refers to the probability of a test correctly identifying those without the disease (true negatives), while sensitivity refers to the probability of a test correctly identifying those with the disease (true positives). Accuracy vs Precision, Reliability vs Validity, True Positive Rate vs True Negative Rate are not the correct terms used to describe this scenario.

28. When discussing the number of women who acquired endometriosis in 2017 divided by the total number of women, are we looking at Incidence or Prevalence?

Prevalence as it focuses on the total number of cases at a particular point in time, regardless of when they occurred.

*That is Incidence as you want NEW cases (in 2017) and you divide by Number of people at risk(ONLY females here).Prevalence would want to know number of all females with endometriosis(not just those who got it in 2017)

Prevalence as it takes into account the rate at which new cases occur over a defined period of time.

Incidence as it involves the total number of cases within a specific population regardless of when they occurred.

Incidence as it considers the total number of cases among a specific group of individuals.

The question depicts Incidence as it relates to new cases occurring within a particular timeframe, in this case, 2017. Prevalence, on the other hand, would encompass all cases regardless of when they occurred.

Explanation

The question depicts Incidence as it relates to new cases occurring within a particular timeframe, in this case, 2017. Prevalence, on the other hand, would encompass all cases regardless of when they occurred.

29. 10 new cases of weird metabolic disease every year, patients on average survive for 10 years. What is the prevalence?

Prevalence=Average duration of disease / Incidence=10/10=1

Prevalence=Average duration of disease + Incidence=10+10=20

*Prevalence=Average duration of disease x Incidence=10x10=100.<Note here that if Duration of disease is short(Like cold) then we can equilibrate prevalence and incidence, while in chronic diseases(Like Diabetes) when duration is long, prevalence is usually larger than incidence.

Prevalence=Average duration of disease - Incidence=10-10=0

Prevalence is calculated by multiplying the average duration of the disease by the annual incidence. This gives us the total number of cases existing in the population at a given point in time.

Explanation

Prevalence is calculated by multiplying the average duration of the disease by the annual incidence. This gives us the total number of cases existing in the population at a given point in time.