Monday, July 9, 2012
Present: Abby Crocker, Amanda Kennedy, Rodger Kessler, Ben Littenberg, Connie van Eeghen
1. Start Up:
a. What are the predictors of successful collaboration within a practice? It’s more than excitement and clearly includes a champion. To be continued…
b. New CTS applicant: surgical resident (Charles Parsons) to start today; will attend the Design class starting this afternoon
c. Questions about opportunities from COM:
i. Laurie St. Gelais: yes, a good opportunity and further discussion is warranted but I deleted the email and can’t for the life of me remember what it is about. Vacation brain syndrome… sorry! Would someone please come to my rescue?
ii. Hilda Alajajian: Emerging Researcher NIH training opportunity to get an insider’s view of NIH study section in the Early Career Review Program. Can be done through training on website.
iii. Ruth Farrell: HHS has new conflict of interest regulations. Information sessions are on Monday, July 9th, 3:30 p.m., Carpenter Auditorium and Wednesday, August 1st, 9:00 am - Carpenter Auditorium. Go if you want to go.
2. Presentation: Abby is working on research articles this summer, one in particular, including the use of STATA. She is looking ahead at her plan for the next few weeks of work. Goal for today: skeleton of the paper and what to move forward without a complete analysis.
a. Check out the “Report in Clinical Usage” book
b. Goal: understand the predictors for neonatal abstinence syndrome that indicate follow up. Essentially: build a model
c. Target publication: Pediatrics. Use the instructions on this web-site to draft the article.
d. Title: A Predictive Model for Neonatal Abstinence Syndrome
e. Background: The 50,000 foot hook (with a number) of why important. What NAS is and how identified. Why the current identification method is sub-optimal. The need for better prediction. “Therefore, we sought to… “ or “Therefore, the purpose of the study is to…” Shoot for three paragraphs.
f. Methods: Description of design, with statement of IRB approval. (This is the place to start, in writing the article)
i. This is a secondary analysis of an existing data set.
ii. Describe the data set as a prospective cohort of women, etc. “To develop our model, we took advantage of an existing data set of pregnant women created for the purpose of… The data were collected through the ICON clinical registry that is a QA registry that includes (# live births for # delivering women)” “Includes all deliveries between 2005 - 2012 of opiate exposed women at FAHC…” “Prospectively collected, with variables including social data about mother, clinical data about pregnancy, delivery, and immediate post-partum period…”
iii. Subject selected (everybody?) with inclusion/exclusion, e.g. mothers not in treatment for substance abuse. Refer to 1st table here? Decide later. “All women in database were potentially included, but we excluded those that (died, didn’t have a chance to develop NAS)” IRB statement follows this description.
2. Predictors (there are many; may need to use a table). Important to identify the starting point of the study: what did you consider.
a. Definitions: what is substance abuse? Defined by opiate dose? Use morphine equivalence? Ask Amanda.
v. Analytic approach.
1. Descriptive statistics: how narcotics were categorized. Use of means and standard deviations for total population of eligible women for this study (770); medians and quartiles; proportions... Box plots… Use of morphine equivalence can also go here.
2. Univariate analysis: Predicting a binary outcome (with and w/out NAS): continuous (t test if it’s normally distributed or use rank based test if not normally distributed) and dichotomous (Chi square, exact test…) Each predictor was analyzed separately with respect to the outcome.
a. Purpose: test each predictor vs. NAS
b. Method: x methods for this analysis
c. Table 1: variables by total with P value in last column
vi. Model building process: P value <=0.10. Binary outcomes can be predicted by one of the following methods: logistic regression, recursive partitioning, and neural networks.
1. Logistical Regression used when all sub-groups are equally predictive, i.e. age of mother is as important a predictor in male vs. female babies.
2. Ben strongly recommends one of the others. To be continued…
g. Results (the rest of the outline will be continued at a later date)
h. Discussion & Limitations
j. Next step:
i. Get organized around the model building process. Meeting with Ben tomorrow.
1. How many variables can this study tolerate before “over-fitting” the model? There are 770 subjects in the data base. About 15. (Over-fitting: fitting random noise into the model. There are ways to minimize this noise, but they have trade-offs.)
ii. Abby will get editing support from Amanda.
3. Workshop Goals for 2012:
a. Journal club: identify UVM guests and articles; invite to CROW ahead of time
b. Research updates: share work-in-process
a. July 12: Rodger – outline of new research paper (Connie by phone, no Abby or Kairn)
b. July 19: (no Abby or Ben)
c. July 26: (no Ben)
d. Aug 2: Abby – “How we picked the predictive model for the NAS article”
e. Aug 9: (no Abby)
f. Aug 16: (no Abby)
g. Aug 23:
h. Aug 30: (new schedule?)
i. Future agenda to consider:
i. Ben: budgeting exercise for grant applications
ii. Journal Club: “Methods and metrics challenges of delivery-system research,” Alexander and Hearld, March 2012 (for later in the year?)
iii. Rodger: Mixed methods article; article on Behavior’s Influence on Medical Conditions (unpublished); drug company funding. Also: discuss design for PCBH clinical and cost research.
iv. Amanda: presentation and interpretation of data in articles
v. Sharon Henry: article by Cleland, Thoracic Spine Manipulation, Physical Therapy 2007
Posted by Connie at 7/09/2012 11:21:00 AM