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The Case For Mammograms: Friends And Family Might Be A Greater Influence Than Doctors

Most women in their 40′s believe they should have annual mammograms, regardless of what screening regimen their doctor might recommend.

So say researchers in Massachusetts who surveyed women (primarily white, highly educated) ages 39-49 presenting for annual checkups. They gave the women a fact sheet about the new USPSTF guidelines on mammogram screening in their age group, and asked them to read one of two articles either supporting or opposing the guidelines. The researchers then asked women about their beliefs, concerns and attitudes about breast cancer and mammogram screening. Here’s what they found –

  • Women overwhelmingly want annual mammograms – Close to 90% of women surveyed felt they should have annual mammograms, regardless of what their doctor might recommend.
  • Women overestimate breast cancer risks – Eighty eight percent overestimated their lifetime risk for the disease, with the average estimate being 37%. (The correct lifetime risk for breast cancer is 12%). This is consistent with previous research on breast cancer beliefs.
  • The media may not influence women’s opinions about screening guidelines – Read more »

*This blog post was originally published at The Blog That Ate Manhattan*

Media Bias Favors Mammography Against The Evidence

A new analysis in the American Journal of Preventive Medicine, “The Public’s Response to the U.S. Preventive Services Task Force’s 2009 Recommendations on Mammography Screening,” included a content analysis of news stories and social media posts around the time of the USPSTF announcement. The authors report:

“Of the 233 newspaper articles, blog posts, and tweets coded, 51.9% were unsupportive, and only 17.6% were supportive. Most newspaper articles and blog posts expressed negative sentiment (55.0% and 66.2%, respectively)….The most common reasons mentioned for being unsupportive of the new recommendations were the belief that delaying screening would lead to later detection of more advanced breast cancer and subsequently more breast cancer-related deaths (22.5%) and the belief that the recommendations reflected government rationing of health care (21.9%).

These results are consistent with previous studies that suggest a media bias in favor of mammography screening.”

Also see an accompanying editorial by Task Force members Diana Petitti and Ned Calonge.

*This blog post was originally published at Gary Schwitzer's HealthNewsReview Blog*

Women Wait A Long Time For Mammograms In New York City

A recent audit of nine NYC’s Health and Hospitals Corporation found City Comptroller Liu described as dangerous delays in women’s health care. It takes too long for women to get screening and diagnostic mammograms.

The 2009 audit found women at Elmhurst Hospital had the longest waits – 50 working days (that would be 10 weeks, i.e. 2.5 months) for diagnostic mammograms, on average. You can find more details here.

According to the Times’ coverage:

Ana Marengo, a spokeswoman for the city’s Health and Hospitals Corporation, which runs the public health system, said that the comptroller’s data was outdated…

At Elmhurst, she said, the wait as of December 2010 was 20 days for screening and 23 days for a general diagnostic test, as opposed to an urgent one. Read more »

*This blog post was originally published at Medical Lessons*

How Experienced Is The Radiologist Who Reads Your Mammogram?

There’s a new study out on mammography with important implications for breast cancer screening. The main result is that when radiologists review more mammograms per year, the rate of false positives declines.

The stated purpose of the research*, published in the journal Radiology, was to see how radiologists’ interpretive volume — essentially the number of mammograms read per year — affects their performance in breast cancer screening. The investigators collected data from six registries participating in the NCI’s Breast Cancer Surveillance Consortium, involving 120 radiologists who interpreted 783,965 screening mammograms from 2002 to 2006. So it was a big study, at least in terms of the number of images and outcomes assessed.

First — and before reaching any conclusions — the variance among seasoned radiologists’ everyday experience reading mammograms is striking. From the paper:

…We studied 120 radiologists with a median age of 54 years (range, 37–74 years); most worked full time (75%), had 20 or more years of experience (53%), and had no fellowship training in breast imaging (92%). Time spent in breast imaging varied, with 26% of radiologists working less than 20% and 33% working 80%–100% of their time in breast imaging. Most (61%) interpreted 1000–2999 mammograms annually, with 9% interpreting 5000 or more mammograms.

So they’re looking at a diverse bunch of radiologists reading mammograms, as young as 37 and as old as 74, most with no extra training in the subspecialty. The fraction of work effort spent on breast imaging –presumably mammography, sonos and MRIs — ranged from a quarter of the group (26 percent) who spend less than a fifth of their time on it and a third (33 percent) who spend almost all of their time on breast imaging studies. Read more »

*This blog post was originally published at Medical Lessons*

Have Mammograms Delivered Their Promised Effect?

A well-done analysis in the BMJ this week calls into question previous research that has been used to tout mammography as an effective tool for lowering breast cancer mortality in Denmark.  That previous study compared breast cancer death rates in Copenhagen, where women were offered screening mammography in 1991, to areas in Denmark where mammograms were not offered until 17 years later, and concluded that the introduction of mammogram screening resulted in a 25 % reduction in breast cancer mortality in screened areas.

The new study adds an additional county where screening was offered (with a little implication that perhaps the previous researchers should have included this other area, but I’ll stay out of the academic finger pointing) and then reanalyzes the data. Read more »

*This blog post was originally published at The Blog that Ate Manhattan*

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