Harms Associated With Conflation of Data

CDC Guidelines Study: The Devil Is in the Details — Pain News Network

Illicit Opioids: The Harms Associated With Conflation of Data – January 17, 2017 – By Stephen Ziegler, PhD, Guest Columnist

The research letter, like many articles authored by those who are rightly concerned about addiction and overdose, begins by asserting that an association exists between increases in opioid prescribing and “large increases in addiction and overdose deaths in the United States.”

However, there are several problems with such a statement. First, association is not causation.

The example given is that fires (symptoms) are associated with fire engines (treatments), yet fire engines don’t cause the fires. As with both pain and addiction, eliminating treatment options, like opioids, does nothing to eliminate the symptoms (pain or addiction).  

Further, it is misleading and harmful to lump all opioids, prescription and illicit, together.

This is a transparent attempt to manipulate the evidence. Illicit drug use has a much different goal than the use of pain medication, so lumping together confuses any possible useful data.

While conflating the two may help create better headlines and fuel the hysteria, such conflation is misleading because studies continue to indicate that two opioids, illicit fentanyl and heroin, are major drivers in the alarming increase in addiction and overdose, not prescription opioids.

Moreover, lumping all opioids together can be harmful because it ignores the size and complexity of the problems associated with the use and abuse of illicit and licit drugs.

Because drug abuse remains a moving target, it is important to draw distinctions between a variety of factors and sources so that solutions can be tailored and refined. One size does not fit all.

Unclear Methodology Used to Classify Comments

Another problem with the JAMA article was the lack of measurement clarity regarding content analysis and how the authors categorized (coded) the comments that were submitted to the CDC during the open comment period.

According to the authors, the comments were classified as belonging in one of four mutually exclusive categories:

  1. “supportive,
  2. generally supportive with recommendations,
  3. generally not supported with recommendations, and
  4. not supportive.”

I find it outrageous that we were not allowed to see others’ comments, but were instead supposed to take the CDC’s word about the consensus opinion. If the consensus had been clear, they wouldn’t hide the comments.

This seems to be censorship at best, and outright lying at worst: there was no way to know if comments were honestly classified as negative or even counted at all.

The secrecy in every step of every piece of what the CDC did is truly astounding. Before this, I’d never imagined my comments being edited and “classified” by the party I’m commenting on. Isn’t this a job for an uninvolved third party?

While it is unclear whether the coding occurred before or after the comments were reviewed, one section of the paper the authors pointed out that about 6% of the comments “were coded as supportive by 1 reviewer and not supportive by the other; a third reviewer adjudicated these cases.”

Since it is likely that the authors were not randomly selected, it remains unclear what criteria was used to adjudicate disputes related to coding, especially when we know that two reviewers were at opposite ends of the spectrum and the coding scheme was central to the study.

Along these same lines, what constitutes opposition to the CDC guidelines? Was opposition binary (yes/no), was it mixed (and if so, where was the line), or did opposition exist along a range (strong or weak)?

When dealing with qualitative data (words as opposed to numbers), there are tendencies in terms of direction, but the devil is in the details.

This is notable because there were likely many different reasons commentators and organizations were not supportive of the CDC prescribing guidelines, such as, but not limited to:

  1. The secretive nature of the entire process
  2. The short time frame the CDC allotted for public comments (initially less than 24 hours)
  3. Allegations that the process violated the Federal Advisory Committee Act
  4. Strong recommendations based on weak evidence
  5. Committee membership that lacked balance and broad stakeholder involvement
  6. An anti-prescription opioid agenda or bias by some committee members
  7. The fixation on dosing limits ignored the problems associated with converting dosage from one opioid to another, the differences in patients, and the potential for unintentional overdose at any dosage level
  8. The lack of balance and selective nature of the literature cited in the guidelines
  9. The failure to recognize that non-pharmacologic therapy and alternatives to opioids may not be effective or covered by insurance
  10. An ironic lack of transparency and full disclosure concerning potential conflicts of interest among those involved in the guidelines at various levels from start to finish

Conclusion

Drug abuse is a highly complex bio-psycho-social phenomenon that requires recognition that not all people, nor problems, are the same.

We must also not lose sight of the fact that

  • millions of Americans are suffering from chronic pain,
  • alternatives to opioids may not be as effective or covered by insurance, and
  • the overwhelming majority who take prescription opioids use them responsibly.

what both the pain community and the substance abuse community need to focus on is finding common ground and forging balanced solutions, since finger pointing, bullying or taking a zero-sum game approach only impedes progress.

Author: Stephen J. Ziegler, PhD, is a Professor Emeritus of Public Policy at Indiana University-Purdue University in Fort Wayne, Indiana.
Dr. Ziegler conducts research, provides continuing medical education, and consults on the topics of opioid risk management and the impact of drug regulation and enforcement on the treatment of pain. He has been published in several peer reviewed journals and serves as a reviewer for several journals such as the Journal of Opioid Management, Pain Medicine, Cancer, and the Journal of Medical Ethics. Prior to obtaining his law degree, Dr. Ziegler worked as a police detective and as a Task Force Officer for the U.S. Drug Enforcement Administration.
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One thought on “Harms Associated With Conflation of Data

  1. Pingback: Updated: Evidence Against CDC Opioid Guidelines | EDS and Chronic Pain News & Info

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