In these re-analyses of COMBINE data, we identified six clinically useful trajectories of any drinking, replicated a three trajectory solution for heavy drinking, showed that naltrexone and CBI increase the probability of lower risk trajectories and established an association between compliance and drinking trajectories. Although the overall conclusions about the efficacy of naltrexone, CBI and acamprosate are consistent with the conclusions drawn based on traditional summary measures, we believe that the application of trajectory analyses to the COMBINE study data helped provide a more complete and nuanced representation of drinking during treatment and the aspects of drinking that the various treatments affected. For example, in the original COMBINE analyses, the overall percentage of days abstinent was high and the differences between treatments, while significant, small. However, the trajectory analyses reveal several patterns of response that vary in the frequency of initial drinking and changes in the frequency over time. The treatments also influenced membership in some but not every trajectory of response, providing insights into how these treatments operate and suggesting that there are subgroups of individuals who derive greater benefit from specific treatments than observed on summary measures averaged over the entire sample. Although we replicated the finding of three trajectories of drinking seen in the VA naltrexone study and the women’s study, for any drinking six trajectories better reflected the data in the COMBINE Study. This could be due to the larger sample size and the fact that there were two levels of behavioral intervention in COMBINE, a low intensity medication management approach (MM) and a more intensive approach combining CBI with MM, whereas the other studies all provided only a more intensive weekly CBI. Consistent with the primary outcome paper, trajectory analysis did not reveal significant effects of acamprosate alone or in combination with other treatments.
Of the six trajectories of any drinking, three reflected trajectories of poor or worsening outcomes. Naltrexone and CBI influenced the probability of being in these less desirable trajectories as is most clearly seen from . Specifically naltrexone alone reduced the probability of being in the “T6: nearly daily” trajectory and in the “T4: increasing to frequent trajectory”. This finding is consistent with a potential mechanism of this treatment, in which decreased reinforcement from alcohol could lead to reductions in drinking (Sinclair, 1990
). Naltrexone has been shown to alter responses to alcohol even after a single dose in the laboratory (Swift et al., 1994
; King et al., 1997
; McCaul et al., 2001) and in clinical trials (O’Malley et al., 1996
; Volpicelli et al., 1995
). It also reduces the probability of continued drinking following an initial episode of alcohol consumption in clinical trials (Anton et al., 1999
) and in laboratory paradigms (O’Malley et al., 2003
; Anton et al., 2004
; Krishnan-Sarin et al., 2007
In contrast, CBI with or without naltrexone reduced the probability of being in the “T5: increasing to nearly daily” trajectory while it did not decrease the probability of being in the “T6: nearly daily drinking trajectory” (). This finding is consistent with the potential mechanism of a behavioral treatment in which learning new skills can prevent relapse in the face of high-risk situations. Unlike naltrexone, which occupies brain opiate receptors after a single dose and therefore may have immediate therapeutic effects, a single session of CBI may be insufficient to prevent early relapse to nearly daily drinking. In CBI, training in new coping skills does not begin until after the first four – five sessions, which focus on building motivation for change and development of a treatment plan (Longabaugh et al. 2005
). As a result, participants who resume nearly daily drinking and potentially discontinue therapy early will not experience the potential benefit of learning new coping skills. In contrast, individuals who receive adequate exposure to CBI will have new tools that they can use to cope with situations that might otherwise lead to escalation of their drinking.
This reasoning may explain why CBI does not significantly change the probability to be in the worst trajectory when compared to placebo. However, it does not explain why the combination of CBI and naltrexone compared to naltrexone alone appears to increase the probability of being in the “T6: nearly daily” trajectory. One can interpret these findings in two ways. If one chooses to focus on the “T6: nearly daily drinking” trajectory by itself, then it seems that CBI may worsen outcome when added to naltrexone. On the other hand, one might choose to focus on the combination of the two worst trajectories (“T5: increasing to nearly daily” and “T6: nearly daily” drinking) since both groups end up with the same undesirable outcome: nearly daily drinking. In this case, looking at the combination of the two topmost bars in by treatment, one can see that CBI decreases the probability of being in the two least desirable trajectories considered together and hence is associated with good outcome overall.
The remaining three trajectories of any drinking reflect outcomes that are more positive. Both naltrexone (alone or in combination with CBI) and CBI alone increased the probability of being in the “T1: abstainer” trajectory and CBI increased the chance of being in the “T2: infrequent drinkers” trajectory. The most novel trajectory identified was the “T3: frequent to infrequent” trajectory in which the frequency of drinking declined over time. Interestingly, naltrexone plus CBI increased the chance to be in this trajectory. One can imagine that naltrexone may have decreased the reinforcing value of alcohol while the new cognitive and behavioral tools taught in CBI capitalized on this effect (or vice versa). Both processes would require some time to have their effect based on an extinction model for naltrexone and a skill acquisition model for CBI. This finding is of note in relationship to the findings of the primary outcome analyses of the COMBINE study (Anton et al., 2006
), in which the combination of naltrexone plus CBI did not improve outcomes across a number of drinking outcome measures over that of either naltrexone or CBI alone. The difference between the present results and those from the primary COMBINE outcome paper highlights the potential benefit of more refined trajectory methods in identifying the efficacy of interventions for drinking subtypes.
As would be expected, baseline drinking was a strong predictor of trajectory membership and was an important covariate in the analyses. For example, individuals with higher days of abstinence pretreatment were less likely to be in the “T6: nearly daily” and “T5: increasing to nearly daily” trajectories, levels of drinking that they did not engage in before treatment.
With regard to trajectories of heavy drinking, the analysis of the COMBINE Study replicated the three trajectory patterns (i.e., “abstainers from heavy drinking”, “sporadic heavy drinkers” and “consistent heavy drinkers”) found in the VA naltrexone trial. Consistent with the results of that study, naltrexone (with or without CBI) reduced the probability of being in the consistent heavy drinking trajectory and increased the probability of being in the abstainer trajectory. CBI without naltrexone also reduced the probability of being in the consistent heavy drinking trajectory and increased the probability of being in the abstainer from heavy drinking trajectory. In contrast to the VA study, naltrexone also reduced the probability to be in the sporadic heavy drinking trajectory, but only in the absence of CBI. It may be that this effect of naltrexone is only evident in combination with less intensive therapy. In the VA Study, all participants received therapy that was more intensive (i.e., weekly Twelve Step Facilitation Therapy and medication adherence counseling).
In contrast to the analyses of any drinking, increasing the number of trajectories was less informative for heavy drinking. For simplicity of presentation, we chose to focus on the three-trajectory solution. Given that heavy drinking is a less frequent event than any drinking, it is perhaps not surprising that we observed fewer trajectories. It is conceivable that additional unique trajectories might be identified in other studies depending on participant characteristics, the treatments studied, and other methodological issues. For example, topiramate studies have enrolled consistent heavy drinkers who were actively drinking at the time of randomization (Johnson et al., 2003
). The application of trajectory analyses to these data might identify a trajectory of heavy drinking in which individuals move from frequent heavy drinking to infrequent heavy drinking or abstaining from heavy drinking.
The contribution of treatment adherence to treatment response has been emphasized for medications (Pettinati et al., 2006
) and for behavioral interventions (Dearing et al., 2005
). To begin to explore this issue, we compared measures of compliance with medication, MM sessions and CBI sessions (for those who received CBI) for the various trajectories of any drinking. With the exception of the number of MM sessions attended for the infrequent drinker trajectory, adherence to each component of treatment was significantly higher in the abstainer trajectory compared to the remaining trajectories. In most studies, those who adhere to treatment experience better outcomes (Zweben et al., 2008
; Fuller et al., 1986
; Cramer et al., 2003
). Adherence to an effective treatment, however, can improve outcomes relative to alternative treatment (e.g., placebo) (Baros et al., 2007
; Volpicelli et al., 1997
). In our analyses, the two trajectories in which drinking worsened over time (i.e., infrequent to frequent and frequent to nearly daily) were associated with the lowest treatment adherence raising the question of whether efforts to promote adherence (e.g., long acting formulations of medications or other behavioral interventions) might be useful in intercepting escalating use if identified early. Based on our analyses we cannot ascertain a causal relationship between compliance and outcome as better outcomes can lead to better compliance just as easily as better compliance can lead to better outcomes. In future analyses, we plan to examine trajectories of adherence to each of the COMBINE treatments and their statistical and temporal association with drinking trajectories and thus attempt to understand the relationship between treatment adherence and treatment outcomes.
Although trajectory analyses provided new information about treatment response, not all questions are answered by this approach. While we can say that a treatment alters the chance to be in a particular trajectory, the results do not tell us what happens for an individual participant. For example, naltrexone reduced the chance to be in the nearly daily trajectory and increased the chance to be in the abstainer trajectory. However, we cannot interpret this to mean that a particular individual will move directly from the daily trajectory to the abstainer trajectory or that a subject might be shifted to a better intermediate trajectory (e.g., frequent to infrequent) while another subject shifts from frequent to infrequent into the abstainer trajectory.
Furthermore, our analysis is predicated on the assumption that different classes of trajectories exist. When no categorically different trajectories exist, a substantial percent of subjects will not be reliably classified into any one trajectory. Our good classification accuracy gives some reassurance that in this study categorically different classes do exist.
Sample size and percent abstainers limit the number and shape of considered trajectories. However, since COMBINE is the largest to date study of pharmacotherapies and behavioral therapies for alcoholism, power to detect distinct trajectories in this study is greater than in most other studies.
Strict inclusion/exclusion criteria in COMBINE resulted in a relatively homogeneous sample of potentially more capable and compliant patients, who were able to achieve four days of abstinence prior to treatment. Thus, the trajectories that we identified and the probabilities of membership in each trajectory may not generalize to a more severe population.
In conclusion, the trajectory analyses provided new insights beyond the original findings from the COMBINE Study, which used more traditional summary outcomes and data analytic approaches. Distinct trajectories of response were identified that were differentially influenced by the various interventions. As such, our analysis of the COMBINE study data highlights the potential value of trajectory analysis as applied to clinical trials.