-- JoAnnAlvarez - 09 Nov 2012

Vanderbilt Center for Surgical Quality Outcomes Research

Projects on their own page

Notes for projects with the Vanderbilt Center for Surgical Quality Outcomes Research

Karen Hoffmann radiation paper

  • on PCOS data (she will also be doing a similar study in the Ceasar cohort, separately.)
  • could also do the same thing w/ surgery
  • Purpose is to report 15 year outcomes on rad patients. Anticipate a small sample size because few patients will survive that long.
  • Also to find predictors of outcomes like functional status
  • Outcomes: sex, urine, and bowel function scores and bother scores. One is 0-100. There are several more domains within each of sexual function, urine, and bowel.
  • Want to look at the outcomes separately by tx: radiation and surgery
  • 3 observations (including baseline?) Some will have only 1 or 2.
  • Need to refine the outcome definition. Percent change? NO! Difference from baseline? Return to bl (Y/N)?
  • Recommended modeling the post rad assessments as a function of the bl assessment (not a change measurement.)
  • I proposed using curveRep()? in rms/Hmisc to show representative curves. Sent email with details to TK.
  • Project 2: looking at radiation patients only, model QOL (functional status) over time as a function of bl function and other bl variables.

CHOICE CEASAR extension grant, Dan Barocas

  • Dan is applying for a new grant. The part we'll be interested in is developing a quality index for research use.

Meeting 2013 June 3

Attending: JoAnn Tatsuki, Dan
  • Ceasar study is an observational comparative effectiveness study of treatments for prostate cancer. It has five sites. Patients are followed over time.
  • Structure: qualifications of MD, resources
  • Process: imaging, lymphadenectomy, communication with PCP
  • Stakeholder involvement:
    • Include patients, payers, providers, hospital administrators
    • Perhaps develop a separate index for each group?
    • They need to help us prioritize the quality measures, and perhaps rank the outcomes in terms of importance –it may be that a composite outcome is best, comprised of urinary/sexual/bowel function, satisfaction, complications and cancer control = QUEST. Patients won't care much about efficiency, but will care about safety. Payers will care about efficiency, and will care about quality and safety as they pertain to cost. etc.
  • Quality Measures: Need to compose a list of candidate measures
  • Independent variables (other than the quality measures): age, race, SES, disease characteristics, psychosocial measures, treatment in some models (some models will apply to only one treatment)
  • Outcome Measures: May need to make a composite of function/complication/satisfaction/cancer control. Alternatively, we could select the most important outcome for each stakeholder group and the others could be secondary - e.g., since virtually all patients survive, we could look at QOL as the main outcome and look at others as secondary
    • Cancer control is one outcome measure. It could be measured by PSA recurrence, need for further therapy, radiographical recurrence, biopsy-proven recurrence.
  • Modeling: Variable selection (beyond the base model) is the key. How to select – stakeholder opinion, a-priori selection, forward or backward stepwise (frowned upon), LASSO (Least Absolute Shrinkage…) technique.
    • Consider one model per stakeholder (with composite outcome) rather than multiple models per stakeholder (with multiple outcomes). But different stakeholders may value different outcomes differently???
  • Order of Operations
  1. Link datasets (Aim 1 of current extension)
  2. Build base model (satisfying Aim 1 and 2 of parent CEASAR grant)
  3. Test individual candidate quality of care measures. These were originally proposed by a Delphi group (perhaps limit to those with satisfactory capture, or those that stakeholders believe have face validity) (Aim 2 of current extension)
  4. Variable selection for inclusion in final model (perhaps with stakeholder involvement)
  5. Build final model, including systematically selected quality measures/ Develop a quality index (Aim 3 of current extension)
    • Could use LASSO!
  6. Measure the contribution to the outcome of the quality measures collectively, and individually.
  • Open questions
    • Optimal method for selecting variables
    • Optimal modeling technique (based in part on whether or not we use a composite outcome; we could select the most important outcome for each stakeholder group and the others could be secondary - e.g., since virtually all patients survive, we could look at QOL as the main
outcome and look at others as secondary)
    • Patient-level model??? Wouldn't it make more sense to develop a quality score for each provider and for each facility??
    • Think about relationship between hospital type (teaching, research, community), travel distance, SES, and outcome. (Travel distance is relatively low priority)

U51 O'Brien grant proposal, Jay Fowke's project

  • This is one of 3 projects in this proposal
  • Looks at associations between obesity and immunologic gene expression in prostate and between gene expression and lower urinary tract symptoms LUTS.
  • How does body fat impact the prostate. (The impact has already been established.)

Meeting 2012 November 12, JoAnn and Tatsuki

  • Read to understand pathway analysis better. They will use a signature t-score method.

Meeting 2012 November 9

  • They will measure gene expression in 511 candidate genes that regulate immune response in prostate tissue.
  • They can probably get about 500 patients, and we need to explain what they can detect.
  • Recruiting mainly at Urology Associates
  • Sample population is patients who get a prostate biopsy that are not found to have cancer or precancerous lesions.
  • Of those biopsied, about one third have cancer.
  • Data collected: interview, chart, blood, urine, bmi, body fat percentage, waist circumference, waist-hip ratio
  • LUTS is measured by a 7-item scale ranging from 0-35. It is right skewed with a mean of 7.
  • Aim 3 involves reassessing LUTS after 5 years. Expect 80% retention for sample size of 400.
  • Gene expression is a count of the affected ___ in each gene.
  • We can use lasso as a variable selection technique to choose the important genes.

Topic revision: r90 - 10 Feb 2017, JoAnnAlvarez
 

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