Last week, we read Chien et al, Efﬁcient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S. I’ve been very interested in these sort of “small-areas” spatial statistical methods recently, so it was good to see what is out there as the state of the art. I think I’ve got something to contribute along these lines some day soon.
Tag Archives: journal club
Journal Club: Efﬁcient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S.
Journal Club: Transmission Assessment Surveys (TAS) to Define Endpoints for Lymphatic Filariasis Mass Drug Administration: A Multicenter Evaluation
While I’m catching up on journal club reading, two weeks ago we discussed Chu et al, Transmission Assessment Surveys (TAS) to Define Endpoints for Lymphatic Filariasis Mass Drug Administration: A Multicenter Evaluation, which takes on the question of how to decide when it is safe to stop a massive disease elimination program. This work must rely on some cool mathematical epi modeling, to say how many years of what level of coverage is necessary before you can hope the LF is gone.
We had a very different sort of research paper in journal club three weeks ago, and I was too busy to jot it down until now. Dewachi et al, Changing therapeutic geographies of the Iraqi and Syrian wars. This is certainly not our usual metrics-heavy approach, so it was good exercise to try to understand it.
Journal Club: Repeat Bone Mineral Density Screening and Prediction of Hip and Major Osteoporotic Fracture
Last week we read Repeat Bone Mineral Density Screening and Prediction of Hip and Major Osteoporotic Fracture by Berry et al. It argues that repeat screening does not improve predictions. But I think the world needs a better way to measure the quality of predictions like these. Area-under-the-curve doesn’t cut it when you are predicting the unpredictable.
Tomorrow is journal club, starting up again for the winter quarter. We are reading Racial Discrimination & Cardiovascular Disease Risk: My Body My Story Study of 1005 US-Born Black and White Community Health Center Participants (US) by Krieger et al.
One exposure paper uses is measured with the Implicit Association Test, which I was trying to explain and couldn’t remember the details of. So I checked online, and learned you can take one yourself! It takes about ten minutes, and may reveal surprising things about you: https://implicit.harvard.edu/implicit/takeatest.html
Journal Club: Meat, fish, and esophageal cancer risk: a systematic review and dose-response meta-analysis
For our final journal club paper of last semester, we read Meat, fish, and esophageal cancer risk: a systematic review and dose-response meta-analysis. I am a vegetarian.
That brings me up to date for fall quarter, and the winter quarter is just finishing its first week. Good!
Journal Club: Investigating health system performance: An application of data envelopment analysis to Zambian hospitals
I’m almost caught up on recording last quarter’s journal club papers, with this second to last topic: Investigating health system performance: An application of data envelopment analysis to Zambian hospitals by Felix Masiye.
This data envelopment analysis (DEA) is an approach I’ve been hearing a lot about recently, and it seems to work through quite an operations-research lens. I hope I’ll be looking into it more in the near future.
Journal Club: Wireless Substitution: State-level Estimates From the National Health Interview Survey, January 2007–June 2010
This National Health Statistics Report that we read toward the end of last quarter’s journal club has one of the driest names we’ve seen. But the topic is a fascinating glimpse into the limits of our knowledge about society. How many households in USA have given up their landline phone entirely and only have a cell phone? Well, we answer most questions like that with a telephone survey. Uh-oh. Fortunately the National Health Interview Survey (in my experience, pronounced most commonly as “en-hiss”) is a health survey were enumerators visit households in person, and even though it is about population health, it can also answer this pressing question about technology use (and the potential invalidity of all of the surveys that do not visit households in person, but just call on the phone).
Continuing to catch up on my record of journal club topics, just under a month ago we read Parental income and the dynamics of health inequality in early childhood–evidence from the UK. There was a discussion of whether this was typical for a health economics paper.
Oh, how the quarter gets away. What happened in our journal club since I last recorded a paper? Well, I will start catching up now. The first thing that happened was just over a month ago we read a paper on prognosis for lovers of survival curves: Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. The author’s interpretation of their results:
Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.