Observational Studies: Cohort vs Case Control Studies

Thank you to Dr Axelrod and Dr Horwitz for two amazing lectures recently!

For Dr Axelrod’s lecture:

Here are the highlights from Dr Horwitz’s lecture:

Standard research study design with associated biases
Standard research study design with associated biases

 

All of the above biases are present in observational studies, but eliminated in RCT

Cohort vs Case Control Studies

Cohort

Risk ratio: Inc dz / everyone exposud vs (Inc of CA among /not exposed )

Case control

Case control easier when incidence is low, and when there is a long time bw exposure and development or dx of illness

Odds Ratio: Antecedent exposure / diseased pts vs antecedent exposure / non diseased (control)

Confounding variables

  • Exposure A is related to another exposure X, which may affect incidence of dz
  • Intermediate confounding: Bias introduced in the intermediate between exposure and outcome state
  • Loss to follow up

Types of Research

Change (Causal) Research

  • Harm: etiologic or risk factor (RR or OR)
  • Diagnostic accuracy
  • Prognosis
  • Therapeutic: Real world evidence vs RCT

Conformity / Consistency Research

  • Quality of Care
  • Inter- and Intra- Observer Variation

Inflammatory Bowel Disease

Thank you to Dr Ehrlich for a very insightful lecture on Inflammatory Bowel Disease (IBD)!

Click here for the lecture powerpoint!

See Lecture Video Database for the lecture recording (coming soon).

Epidemiology

  • 1.4 million people in US
  • Urban population
  • Northern climates
  • Bimodal age incidence distribution
    • 15-30 yo
    • 50-65 yo
  • No known dietary triggers. So for the most part patients can eat whatever they want.

Disease Characteristics

  • See powerpoint Slide #5 for table describing differences between UC and Crohn’s.
  • Note: Patients are at increased risk of cancer due to chronic inflammation

Medications for Ulcerative Colitis (UC)

Topical Medications

  • 5asa suppository or enema
  • Steroid suppository, foam, enema

Oral Medications

  • 5-ASA
  • Immunomodukators (6mp, azathioprine)
  • Steroids
  • Cyclosporine (rarely used anymore)
  • Methotrexate
  • Biologics (Anti TNF alpha inhibitors):
    • Infliximab (IV infusion)
    • Adalimumab (SC injection)
    • Golimumab: similar to the other drugs on the market
  • Budesonide MMX: newer agent; tablet that only gets released when it hits the colon. For mild to moderate UC. Use as an adjunct to 5asa to get pt back in remission

Treatment Strategy:

  • Combination oral and topical initially. Then just oral when it’s better controlled
    Avoid steroids if possible

Medications for Crohn’s Disease

Topical Medications

  • Only useful in Crohn’s Colitis.

Oral Medications

  • Immunomodukators (6mp, azathioprine)
  • Steroids
  • Antibiotics
  • Methotrexate as adjunct
  • Biologics (anti TNF alpha: Infliximab (IV infusion),  Adalimumab (SC injection)
  • Natalizumab: causes pml so not used anymore
  • Vedolizumab: antibiotics integrin prevents leukocyte tracking. Similar to natalizumab, but specific to the gut. No PML so far. IV on weeks 0, 2, 6 and every 8 weeks thereafter
  • More effective in UC compared to crohn’s
  • Ustekinumab (Stelara) il 23 inhibitor, previously approved for psoriasis. Note at a higher dose for crohn’s.
  • Check out the Uniti1 and Uniti2 Trials for more information

Health Maintenance in IBD Patients

Vaccines in Immunosuppressed Patients

As is inherent in the term, the immune response is blunted with immunosuppressives and thus live vaccines are contraindicated.  BUT, there is no evidence that giving a vaccine will cause an IBD flare.

Definition of immunosuppression:

  • Prednisone 20mg daily for two or more weeks and within three months of discontinuation
  • Treatment with immunomodulators or biologics and within three months of discontinuation
  • Significant protein/calorie malnurition

And other vaccines are contraindicated in immunosuppressives

Inactivated vaccines are able to be given in immunosuppression:

  • Ex: TDaP, HPV, Influenza, Hepatitis A, Hepatitis B, Pneumococcal

Live vaccines should NOT be given in immunosuppression:

  • Ex: Varicella, Herpes Zoster, MMR

Bone Health in IBD

Assess bone density (via DEXA) in the following conditions:

  • Total steroid use >3 months
  • Inactive disease but past chronic steroid use of at least 1 year but within the last 2 years
  • Inactive disease but maternal history of osteoporosis
  • Inactive disease but malnourished or very thin
  • Inactive disease but amenorrheic
  • Post menopausal women regardless of disease status

Skin exam yearly if on immunosuppressed

Colonoscopy and Cancer Screening in IBD

  • IBD with greater than 1/3 of colon affected? If yes, then start colon cancer screening 8 to 10 years after initial diagnosis. Then, screen every 1-2 years.
    • Chromoendoscopy preferred
  • Tobacco cessation
    Depression screening

Tidbits on Medications

  • 5-ASA: commonly causes renal insufficiency (check once yearly Cr)
  • Immunomodulators (AZA, 6MP, MTX): monitor for blood and liver abnormalities;  cancer(lymphoma), pancreatitis
    • Check these tests weekly for a monthly then space out
  • Anti-TNF alpha: Check HBV and TB before initiation

IBD during Pregnancy

  • MTX absolutely contraindicated
  • Sulfasalazine causes reversible azoospermia in men
  • Key Point: Keep sxs controlled. Most meds can be continued during pregnancy

Chief’s Case 10-11-16

First Chief’s case of the season is over and done.  The focus was on clinical reasoning and going through the steps of creating an appropriate problem representation, that leads to a differential diagnosis, which then triggers illness scripts.

Clinical Reasoning Tips to take away:

  1. Problem Representation-  Create an effective “1-liner” about the patient and their story
    1. Salient features- i.e. fever, rash, lab abnormalities
    2. Temporal relation of conditions
    3. Syndrome
  2. Illness Scripts- mental summary of a provider’s knowledge of a disease
    1. Predisposing conditions
    2. Pathophysiological insult
    3. Clinical consequences

Example from Chief’s Case (Malaria):

Problem Representation:

  • 29 year old pregnant female, recently traveled to Sudan, presents with ~1 week of fever, shortness of breath, epigastric pain, found to have elevated total bilirubin, metabolic acidosis, anemia and thrombocytopenia.

Illness Script:

  • Malaria
    • Pathophysiology- plasmodium infection, transmitted by mosquitos, going to liver and then invading RBCs
    • Epidemiology- endemic areas (Sub-Saharan Africa and Southeast Asia), increased infection for young children, immunocompromised, pregnant women.
    • Time Course- days to weeks, can lie dormant (P. vivax or P. ovale) for months in liver
    • Salient symptoms/signs- fever, chills, nausea/vomiting/diarrhea, abdominal pain, tachycardia, tachypnea, headache
    • Diagnostics- anemia, thrombocytopenia, LFT abnormalities, U/S with hepatosplenomegaly.  Thick/thin smear (x3 to completely rule out).
    • Treatment- depends on resistance pattern and pregnancy status.  Will need definitive treatment for dormant liver parasites.

Thank you for the expert opinion from Drs. Dan Mueller and Bizath Taqui!

Updates on Fecal Microbiota Transplant

Microbiome is the ecological community of commensal, symbiotic, and pathogenic microorganisms that share our body space.

Clostridium difficile epidemic (30,000 deaths/year), with a cost of $5.2 billion annually.  Recurrence rate 15-35% and increase up to 45-65% after more than one episode.

Risk factors- antibiotic use, hospitalization/health care exposure, long term care facility resident, advanced age, PPI use, IBD, pregnancy, immunocompromised.

Decreased fecal diversity noted in C. diff, with further decreases in diversity with recurrent infections.

Fecal microbiota transplant (FMT) can work because normal fecal flora may “out compete” C. diff.  There could be production of antimicrobials or an increase in secondary bile acid production

Indications for FMT:

  • Recurrent or relapsing CDI- 3 episodes of mild to moderate C. diff infection or 2 episodes of moderate to severe.
  • Moderate C. diff not responding to therapy for 1 week
  • Fulminant cases not improving in 48 hours

Results from data collected for OpenBiome (the main stool banking company) shows an overall clinical cureof 84% with a single treatment.  Lower GI delivery had superior results.

Risk factors for failure included severe/complicated disease, prior hospitalization for C. diff, being inpatient.

Risk of recurrent C. diff is increased by post FMT antibiotic use.  Risk is unchanged if there is prophylactic use of C. diff antibiotics or probiotics.

Use of FMT in patients with IBD has shown a significant improvement in steroid free clinical remission and endoscopic response/remission

ACP Best Practices for Pulmonary Embolism

Check out the best practices at: http://annals.org/article.aspx?articleid=2443959

ACP Best Practices for Pulmonary Embolism:

  1. Use validated clinical prediction rules to estimate pretest probability
  2. Do not obtain D Dimer or imaging in patients with low pretest probability of PE and meet PERC RO criteria
  3. Get a D Dimer, and NOT imaging in:
    1. Moderate pretest probability
    2. Low pretest probability who do not meet all PERC rule out criteria
  4. Use age adjusted D dimer thresholds in patients >50yo
    1. Calculation: Age x 10ng/mL
  5. Do not get imaging in patients with D Dimer below age adjusted cutoff
  6. If high pretest probability, then:
    a. Get CT angio pulm arteries
    b. V-Q scan if cannot get CTPA
    c. Do not get D Dimer

Biostatistics – Making the Diagnosis: Bayesian Statistics

This is a confusing topic that is at times difficult to wrap one’s head around.  We likely created some confusion around the topic during lecture so here is a stepwise are the key points.  So, let’s walk through.

When do I use Bayesian Statistics?

Believe it or not, you likely already use them on a day to day basis–you probably just don’t quantify them as much.  Every time you make your differential diagnosis, you determine what you think the likelihood is of a particular diagnosis (ie – pretest probability).  You make decisions on which test to order all the time based on that.  Then, you use the sensitivity and specificity of the test to determine if that diagnosis is ruled out or if you want to pursue another test (ie – post test probability).

What are Bayesian Statistics?

First, let’s go over some definitions.  Don’t memorize all of this right off the bat.  Feel free to refer back to it.

  • Pre-test Probability: probability of a patient having a particular diagnosis. Sum of all pretest probabilities on the differential is 1.
  • Post-test Probability: probability of a patient having a particular diagnosis, adjusted for the results of the test performed.
  • Likelihood Ratio (LR): the ratio that changes our initial estimate of the likelihood that a patient has a condition (ie – pretest probability) to a more accurate estimate (ie – post test probability)
    • Positive LR: likelihood ratio for a positive test result
      • = Sensitivity / (1 – Specificity)
      • aka: probability of a aka: probability of having a positive test on a patient with a disease / probability of having a positive test in a patient without the disease
    • Negative LR: likelihood ratio for a negative test result
      • = (1 – Sensitivity) / Specificity
      • aka: probability of having a negative test in a patient with a disease / probability of a negative test in a patient without the disease
  • Bayes theorem merely states that the post test probability is affected by the pre-test probability and the likelihood ratio of the test you performed.

How do I use Bayesian Statistics?

Now that we’ve gone over the definitions, let’s walk through how you’d use Bayesian Statistics when diagnosing a patient on the floors.

1. Assess your pretest probability of the patient having Disease X.  Two Primary Methods:

  1. Use your gestalt. That is, your clinical judgment.
    1. Note: This is susceptible to bias (eg – priming of recent experiences, traumatic/emotional experiences, insufficient weight on new evidence) and random error.
  2. Evidence. Complementary Approaches
    1. Use Clinical Decision Rules / Prediction Rules
      1. Ex: Well’s, C spine rules, Ottawa foot and ankle rules
    2. Find research with patients with the same clinical problem. These studies list the frequency of diagnoses and odds ratios based on certain characteristics.

2. Find or calculate the Likelihood Ratio.

Find in the literature or in UptoDate the likelihood ratio of your test being positive (+LR) or negative (-LR).  If you cannot find this, the sensitivity and specificity can easily be used to calculate it (see calculations above)

3. Calculate your Post-Test Probability.fagan-nomogram

This is likely where the confusion arose in lecture.  We didn’t have time to put up the Fagan Nomogram during lecture but I’m sure it will help elucidate.

In a nutshell, the left hand side is the pretest probability.  In the center you’ll find the likelihood ratio.  On the right is the post-test probability.

To use the nomogram, take a ruler and line it up with your pre-test probability and the calculated likelihood ratio.  Draw a line into the third column to find your post-test probability!

See examples below!

 


 Example: Pulmonary Embolism

Check back soon!


Resources:

JAMA User’s Guide to the Medical Literature: Essentials of Evidence Based Clinical Practice

Annals of Internal Medicine 2015 – Evaluation of Patients With Suspected Acute Pulmonary Embolism: Best Practice Advice From the Clinical Guidelines Committee of the ACP