Duke Research - May 2011

May 31, 2011

Women's Health in Pakistan

Guest Post by Chanel Laguna, NC Central University summer intern

Mothers and other women are dying from preventable causes in Pakistan because their lives are not valued, obstetrician Shershah Syed told Duke Global Health symposium on May 25.

Syed, who works at the Koohi Goth Hospital in Karachi and the former president of the nation's Society of Obstetricians & Gynecologists, said the women suffer from a lack of medical assistance and abandonment by their husbands, fathers and brothers.

These problems were made worse by the massive flooding of 2010. He showed the global health meeting a video of his work in Pakistan's remote villages during that crisis. Those who survived the flooding in cities such as Sindh and Sukkur were left without food and medical supplies.

This need caused Syed to set out on a mission to deliver packages of medical resources to those who were left homeless. “This situation is so sad," Syed said. "One-third of these people are living below poverty.”

He says it’s disturbing to think how such affluent countries like India and Pakistan could have many areas below the poverty level. “These are rich countries, but their priorities are wrong.”

Less than 6% of spending in Pakistan goes towards medical care and less than 2% in education. Syed wants to see change.

“The solution lies in the government,” said Syed. “The money given from donors should go towards women and education; instead it ends up in the government’s hands.”

Syed

Syed made it clear that there is a lack of trust when it comes to government spending. Donors who contribute to these issues are skeptical to give money due to this lack of trust.

Members of his audience agreed. “The U.S. government should increase accountability for aid to Pakistan as its aid is not making the desired impact,” said Bassam Fawad, a Fuqua School of Business student who is married to Syed's niece, Sana.

Syed said more needs to be done to improve women's health care, and the first step is education.

He said mens' attitudes towards women stem from a lack of education. Many are unable see the value in women and treat them poorly.

“In Pakistan, we want women who are happy and competent in society," he said. "We are a long way from that.”

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May 19, 2011

Changing how students talk about science

By Ashley Yeager

College is where students practice being scientists and engineers. It's like riding a bike with training wheels.

But Cary Moskovitz, who directs Writing in the Disciplines at Duke, argues that if students are to learn to communicate science well, they need to practice writing like professional researchers. In other words, they need to lose the training wheels a lot sooner.

Moskovitz says that students have been getting more inquiry-based laboratory training in the last 20 to 30 years, but lab reports have not evolved much at all.

"The actual writing that tends to be done in association with these labs still tends to be limited more towards the traditional school lab report, which is a kind of writing scientists don't do," Moskovitz said in May 19 during the Science magazine podcast.

He and co-author David Kellogg, who teaches English at Coastal Carolina University in Conway, South Carolina, also argue in the magazine's weekly Education Forum that writing lab reports in science classes needs to be better structured. They suggest that lab reports will be more "authentic" if students are writing in a variety of genres that scientists actually use to communicate – experimental reports, methods papers, proposals and peer reviews. They also argue that students should be treated as "apprentice scientists," where their instructors are not graders, but readers who scrutinize the students' work as scientists.

"We think instructors should think about the instruction of scientific writing longitudinally throughout the curriculum, rather than for each lab or individual course," Moskovitz told Science.

The authors admit that changing lab exercises to integrate this type of writing component would be difficult and would require another level of training for teaching assistants. But, the authors write in their forum, "If we are serious about improving students' abilities as scientiﬁc communicators, we must take them seriously both as apprentice scientists and as apprentice writers of science."

Click here to listen to the full Science Podcast.

Citation: Moskovitz, C. and Kellogg, D. "Inquiry-Based Writing in the Laboratory Course," Science. Vol. 332. 20 May 2011. DOI: 10.1126/science.1200353

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Tags: science communication & education, students

May 2, 2011

Statisticians Review Landmark HIV Vaccine Trial

Hopes ran high in 2009 when a New England Journal of Medicine article announced success in developing a vaccine against HIV, the virus that causes AIDS.

But a new Bayesian statistical analysis initiated at Duke demonstrates that the results were far from conclusive.

“The world has been waiting for an HIV vaccine for almost 30 years,” said Victor DeGruttola, a biostatistician at the Harvard School of Public Health who participated in the new analysis. "Its efficacy is an emotionally charged issue.” The HIV vaccine study, called RV 144, had been viewed as the “first evidence that suggested we were close."

New analysis of the RV144 data shows it is more likely that the vaccine actually has no effect compared to what was presented in the initial analysis. The new analysis also highlights the need to regularly use multiple statistical methods to review new medicines, said James Berger, a statistician at Duke University who spearheaded the study along with Peter Gilbert of the University of Washington and DeGruttola.

The results appear in the April 1 issue of the Journal of Infectious Diseases. The new analysis uses Bayesian statistics, which includes information from the original data and also data from previous HIV vaccine research.

The original RV144 study reported new HIV infections in 51 of the 8,197 volunteers given the vaccine versus 74 of the 8,198 participants given the placebo. These results suggested that the vaccine, a combination of two other failed vaccines, was 31.2 percent effective, with a p-value of .04. Many researchers and journalists interpreted the statistics to mean that there was only a four percent chance that the vaccine was not effective, and alternatively a 96 percent chance that it was 31-percent effective.

“But it’s not that simple,” DeGruttola said. He was dismayed with the interpretation and criticized it in the journal Science. He said the correct way to think about the numbers is to assume the vaccine does nothing. “Assume it is water. Repeating the experiment 50 times, researchers would expect that one out of 50 times they'd find equal-to or greater-than 31.2 percent vaccine efficacy,” he said, adding that these standard statistics ultimately say nothing direct about whether the vaccine works.

Berger said Bayesian analysis improves upon the standard statistical methods because it can make statements about the chance that the vaccine had some efficacy. The P-values, which were used in the original analysis, cannot. In the new analysis, the researchers explain that the p-value of 0.04 was misinterpreted and say that, using Bayesian statistics, there is no more than a 71 percent chance that the vaccine was effective at preventing HIV.

In other words, there is a 29 percent chance that the vaccine was not effective, not a 4 percent chance, he said.

Because of what is at stake in HIV vaccine research, the conversation related to RV144 has not always been as scientific as it could have been, Gilbert said. He has reviewed and devised HIV vaccine trials since 1996 and said the new analysis provides statisticians and non-statisticians with a “golden opportunity” to have rational, scientific, and careful discussions when determining “false positive flukes” versus real effects.

“The new evidence doesn’t give us any reason for great joy, or greater gloom,” said De Gruttola, but the researchers agree that the Bayesian analysis provides a new framework to add increased rigor into future vaccine trials.

CITATION: "Statistical Interpretation of the RV144 HIV Vaccine Efficacy Trial in Thailand: A Case Study for Statistical Issues in Efficacy Trials," Peter B. Gilbert, James O. Berger, et al. Journal of Infectious Disease, Vol. 203, Issue 7. doi: 10.1093/infdis/jiq152

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Tags: global health, health, research