An Approach to Evaluate the Effects of Concomitant Prescribing of Opioids and Benzodiazepines on Veteran Deaths and Suicides (2019) / Chapter Skim
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3 Observational Emulationof the Target Trials and Practical Considerations
3 Observational Emulationof the Target Trials and Practical Considerations
Pages 71-98
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From page 71... ...
While this chapter does not define a specific analysis strategy, as the committee was not charged with conducting the actual analyses and did not review the VA's databases, it does lay out considerations of how to emulate each of the components of the protocol of the target trial: eligibility criteria, treatment strategies, treatment assignment, follow-up, outcomes, causal contrasts, and statistical analysis plan. Before the committee describes the emulation procedures for each component of the target trials, it is important to note that the target trials described in the previous chapter (see Table 2-3)
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From page 72... ...
DATA SOURCES Potential sources for data key to the observational emulation of the target trials from 2010 through 2017 are the VA Corporate Data Warehouse (CDW) , the outpatient prescription data from the VA's Pharmacy Benefits Management Services, and the Centers for Disease Control and Prevention's National Death Index (NDI)
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From page 73... ...
In cases where a single patient is eligible at multiple times for the same study, one of the multiple eligibility time points could be chosen at random to serve as baseline for that patient, or, alternatively, multiple eligible time points could be included in the emulation.1 1 See Hernán and Robins (2016) for further discussion.
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74 FIGURE 3-1 Opioid treatment initiation and tapering study schematic. NOTE: NSAID = nonsteroidal anti-inflammatory drug.
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EMULATING THE INITIATION AND TAPERING TARGET TRIALS Tables 3-1 and 3-2 reiterate the specification of the components of the target initiation and tapering target trials, already described in Table 2-3, and delineate the emulation procedures using available observational data. That is, the target trial columns of Tables 3-1 and 3-2 replicate the relevant columns in Table 2-3, and the last column in each of the tables outlines the proposed observational analyses to emulate the eligibility criteria, treatment strategies, treatment assignment, start and end of follow-up, outcomes, causal contrasts, and statistical analysis of the target trials.
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Treatment Individual randomization Assumed to be random conditional on assignment baseline confounders, including, but not limited to -- Medical illnesses -- Mental health diagnoses -- Pain intensity -- ubstance use disorder (SUD) S diagnoses -- istory of overdose with prescribed H opioid -- Medication history -- Age Diagnoses associated with clinical visits in VA medical records will be used to define these variables.
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Per-protocol effect to-treat effect: this effect may be close to null and therefore relatively uninformative because adherence to the assigned treatment strategies is expected to be low in the observational data. Observational analog of the per-protocol effect.
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potential selection bias induced by censoring, inverse probability All variables will be obtained from weighting will be used. The medical records, including clinic visit weights will be a function of the information, diagnoses, and pharmacy baseline and post-baseline (time- records.
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Exclude: Individuals with serious illnessc Individuals prescribed opioids for the treatment of opioid use disorder Individuals with surgery or acute painful injury within the 90 days prior to baseline Treatment (a) No dosage reduction: ≤5% The treatment strategy to which a strategies average decrease per month for participant is assigned is determined by 3 months the average change in opioid dose during (b)
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Per-protocol effect to-treat effect: this effect may be close to null and therefore relatively uninformative because adherence to the assigned treatment strategies is expected to be low in the observational data. Observational analog of the per-protocol effect.
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Per-protocol analysis: patients will be censored at the time All variables will be obtained from they deviate from their assigned medical records, including clinic visit strategy. To adjust for the information, diagnoses, and pharmacy potential selection bias induced records.
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TREATMENT STRATEGIES Emulating the initiation and tapering target trials requires using information from VA pharmacy data to determine the treatment strategy. The pharmacy data contain information on medications filled and dispensed to VA patients, either in VA facilities or through mail order, with data fields such as the date dispensed, days supplied, number of units, and dose per unit.
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From page 83... ...
Figure 3-2 illustrates multiple hypothetical trajectories of opioid use patterns over time that are relevant to this study, with the vertical axis representing dose and the horizontal axis representing time. The top several trajectories depict monthly averaged dosages over the observation period from which the intended course of treatment is relatively easy to infer and that are consistent with protocols for the tapering target trial.
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Sensitivity analyses can assess the impact of measurement decisions on the study conclusions. For example, alternative measurements of treatment strategy may assume that medications prescribed to be taken "as needed" are taken by the patient at a faster (e.g., maximum
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For example, a physician's impression that a patient is misusing his or her opioids -- an impression that is likely to affect the choice of treatment strategy and may be correlated with other patient characteristics that affect outcome -- would be an unmeasured confounder if the physician impression is not recorded in the medical record or is otherwise unavailable to the investigator. It would be partially measured if it were recorded in some medical records but not others or if only indirect indications of the physician's impression were available.
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From page 86... ...
For each example provided below, the committee considers how it might relate to opioid initiation and tapering and to outcomes of suicide and all-cause mortality. Examples of Measured Confounders Medical Illnesses Co-existing medical illness may affect the opioid treatment approach in several ways.
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. Given the comorbidities that are more prevalent in patients with a history of prescribed opioid overdose (psychiatric illness, opioid misuse, substance use)
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. Opioid Misuse Behaviors Although some opioid misuse behaviors are easily found in the medical record (e.g., having gone to multiple clinicians for opioid prescriptions, missed appointments, illicit substance use)
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; that is, it will be done by comparing the outcome distributions between groups defined by the treatment strategy assigned at baseline. The main difference between how the target trial and observational analog would be analyzed is that the observational analysis will require an adjustment for baseline covariates that are imbalanced across the different treatment strategies.
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From page 90... ...
Key inputs for evaluating the adequacy of the sample size for conducting an informative analysis include the number of eligible patients per analysis, the comparability of patients across the treatment strategy groups, the expected value of the outcome, the size of a clinically meaningful effect of one treatment strategy versus another on the outcome, and the variation in the outcome. That assessment of the magnitude of an effect is illustrated by considering all-cause mortality in the context of the dosage reduction study.
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From page 91... ...
Nevertheless, the calculations demonstrate the challenge posed by examining rare outcomes. Limitations The approach described in this chapter, namely the emulation of particular initiation and tapering target trials using observational data and analyses, comes with limitations that relate to the risk of bias in nonrandomized studies of interventions (Sterne et al., 2016)
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From page 92... ...
For the tapering study specifically, the appropriate classification of the intervention categories represents a specific challenge as it requires inference of the intended treatment strategy (e.g., continuation, slow taper, fast taper, etc.) from multiple consecutive prescription fills (see Table 3-2)
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One must assess a priori whether there would be a sufficient number of patients in the database to detect a clinically meaningful effect when emulating the target trial. Generalizability The interpretation of findings from the emulation of the target trial using observational data must take into account how generalizable the study's findings would be.
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opioid dosage tapering in patients receiving chronic benzodiazepine treatment, and the committee developed protocols and analytic strategies for those trials, while recognizing that many other studies are of potential interest. The object of the trials is to determine preferred approaches for opioid initiation or tapering strategies for patients participating in the trials, while taking into account the potential limitations of the available observational dataset.
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The proposed observational studies has the potential to reveal important insights that could help health care providers improve chronic pain treatment by beginning to understand the most appropriate role of opioid treatment in a comprehensive program of chronic pain management. REFERENCES Aspinall, S
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2006. Predictors of opioid misuse in patients with chronic pain: A prospective cohort study.
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2012. Prescribed opioid difficulties, depression and opioid dose among chronic opioid therapy patients.
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2012. Prescription opioid abuse in chronic pain: A review of opioid abuse predictors and strategies to curb opioid abuse.
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