On Relapse Rates and Sobriety Goals

Relapse in substance abuse is far from failure. Not only does relapse provide an individual with a chance to change, but it provides valuable information about the effectiveness of treatment. Even better, relapse rates may be able to provide addicts with a timeline of sobriety goals to aid in recovery.

Addicts need to know if, and how, their chances for success increase over time. An opiate addict is likely to hear that he or she has an 85% chance of relapse. While this is valuable for evaluating the effectiveness of treatment, hearing one’s likelihood for failure doesn’t exactly bolster confidence.Solutions for Extreme Conditions = Experience + Innovative Thinking

A more fruitful statistic for an addict would be, “Opiate addicts are ___% less likely to relapse after one year following treatment.” One year becomes a benchmark, a goal, for the recovering addict to achieve. Phrased as sobriety goals, statistics on relapse rates could potentially be very helpful for recovering addicts.

This is simple enough to say, but the data is complicated.

Relapse rates are usually reported specifically per substance, and many compare relapse rates between treated and untreated individuals for a substance. This is further complicated in that different treatment methods might be used in different studies, and individuals don’t always remain in treatment for comparable amounts of time.

The following statistics give one an idea of these difficulties, as well as an idea of relapse rates for alcoholism:

  • According to this source updated in 2014, 80% of patients with alcohol addictions relapse within the first year. After 2 years, however, this relapse rate drops to 40%. Patients are 40% less likely to relapse after two years of sobriety. This rate drops even further after 5 years, though a statistic is not provided.
  • This 2006 study found that by year 3, 62.4% of individuals in a treated group were remitted in addition to 43.4% in the untreated group. Unfortunately, in year 16, the number of sober individuals in the treated group dropped to 35.6% and 17.1% in the untreated group. According to this study, patients are about 26.3% more likely to relapse in year 16 than in year 3.

The information above illustrates the difficulty in determining reliable relapse rates even within one addiction such as alcohol. Patients referenced in the first source were likely given different treatment than the second source. Furthermore, the time frames are completely different; the first source informs us of the change from year 1 to year 2, and the second details the change from year 3 to year 16.

What is ultimately needed is a detailed meta-study focused on providing addicts with benchmark statistics, specific to their addiction, to encourage them to last just one year, two years, five years longer. Addicts need to know when the temptation to use will get easier to refuse. Descriptive statistics such as these would also be the lowest-cost means of tracking progress each year of sobriety.

More recent research may offer more personalized estimates of relapse risk, though potentially more expensive. According to an article published in February of 2011 the extent of grey-matter deficits in alcoholics, particularly in the part of the brain regulating behavioral control and decision making, predict the likelihood of relapse.

“Hazard ratios indicated that, for each 1ml reduction in grey-matter volume in the medial frontal cluster and in the parietal-occipital cluster, there was a 48% increase in risk of earlier relapse. After further adjustment for years of alcohol use and total alcohol consumed in the 90 days before treatment, smaller grey-matter volume in these two clusters predicted shorter time to relapse to heavy drinking, by 44% and 45% respectively.” –Rando et al.

Rather than searching for generalized averages to indicate a person’s risk of relapse, doctors could analyze an addict’s grey-matter volume in the parts of the brain mentioned above to determine risk level.

Furthermore, if an addict is introduced to a program that helps increase grey-matter volume, he or she could see his or her risk level drop as the program progressed. Perhaps, for each 1ml increase in grey-matter volume, there is a 48% decrease in risk of earlier relapse. Mindfulness practice has been shown to cultivate an increase in grey-matter density.

Measuring grey matter may be one of the most accurate predictors of relapse risk, but most addicts don’t have the money for such a detailed and personalized consultation. The above study is also specific to alcoholism, leaving other addictions in the dark.

Fortunately for addicts and families alike, research on addictions continues to expand. Data on relapse rates is currently scattered and disparate, but with careful analysis a series of meta-studies could piece the patterns together. There is a need for more positive analysis of relapse patterns. What’s needed are descriptive statistics to give addicts hope, and goals.

Laurel Sindewald is a writer, musician, philosopher, and biologist.

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