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Prepared by:

Schedule II Opioids and Stimulants & CMV Crash Risk and Driver Performance:

A Review of Findings for the Medical Review Board

July 29, 2014

+Roadmap

Purpose

Background

Overview of Research Questions

Search Methodology

Q1a

Q1b

Q2

Q3

Conclusion

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+Purpose

FMCSA asked Acclaro Research Solutions, Inc. to conduct a systematic literature review

The review looks at how the licit use of Schedule II opioids and stimulants may impact the risk of CMV crashes or indirect measures of driver performance

These findings, along with input from an expert review panel and FMCSA’s Medical Review Board, are used to inform policy and decision-making

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+Background

Schedule II Drugs Controlled Substances Act (CSA) became law in 1970

Regulates the manufacture, possession, importation, and distribution of certain substances

5 classifications (schedules) of controlled substances

Schedule II drugs have medical application but also carry a high risk for both psychological and physical dependence

Schedule II includes a variety of stimulants, depressants, and a large number of opioids

This study focuses on Schedule II opioids and stimulants

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+Research Questions

Q1a: What is the relationship between licit use of prescribed Schedule II opioids or stimulants and the risk of a motor vehicle crash?

Q1b: What is the relationship between licit use of prescribed Schedule II opioids or stimulants and indirect measures of driver performance?

Q2: Are the effects of licit use of prescribed opioids or stimulants measureable by serum levels? Do these effects remain consistent or vary based on metabolism or other pharmacokinetic parameters?

Q3: Do the effects worsen or improve when: 1) drug-drug interactions take place with other Schedule II or over-the-counter medications; or 2) the drug has been chronically administered over a period of time (stable use)?

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+Search Methodology

Defined search terms a priori "potentially driver-

impairing" OR "PDI" OR "drug driving" OR "drugged driving"…

Systematically searched for full-length articles published January 1, 2006 to December 2013

Retrieved abstracts reviewed for inclusion/exclusion

Articles meeting inclusion standards were retrieved in full text and reviewed thoroughly for final inclusion

Included articles evaluated for quality of evidence

Research databases (n=11) Academic Search Premier,

Business Source Complete, Cochrane Library, CINAHL, Embase, Health Business Elite, National Guideline Clearinghouse, PubMed, ProQuest, Science Direct, TRID

Commercial, non-profit, and government websites (n=18) National Transportation Safety

Board, American Pain Society, FMCSA, FDA, American Trucking Association, etc.

Reference sections of all included articles

Search Strategy

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Sources Searched

+Search Methodology

Published in English Full-length articles n=10 or more subjects

enrolled Most subjects must be 18+ Study on the licit use of

prescribed Schedule II opioids or stimulants If illicit use is included, the

effects must be separable If drugs other than Schedule II

opioids or stimulants are included, the effects must be separable

Published after January 1, 2006 The most complete publication

will be the primary reference

Inclusion Criteria

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+Evaluation of Quality of Evidence and Characterization of Evidence Included articles were reviewed for bias using the standards

of the Cochrane Bias Methods Group Studies rated in discrete categories such as selection bias,

attrition bias, reporting bias, etc. All studies were deemed acceptable quality and none were

dropped Overall body of evidence for each research question and topic

was rated on a four-point scale: Strong: Evidence is convincing; highly unlikely new

evidence will change conclusions Moderate: Evidence is somewhat convincing, small chance

new evidence will change conclusions Weak: Some evidence exists, but there is a reasonable

chance new evidence would overturn conclusions Unacceptably Weak: Insufficient evidence to draw

conclusions

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Research Question 1aWhat is the relationship between licit use of prescribed Schedule II opioids or stimulants and the risk of a motor vehicle crash?

Evidence base n=25

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+Q1a: Opioids & Crash Risk10

 Opioid use & driver

fatalityOpioid use & driver

injuryOpioid use & crash

riskOpioid use & unsafe

driver actionsOriginal Research

Articles

(n=3) All found significantly

increased adjusted OR [*4, *6, 12]

* Two studies used same data set

(n=5) Found significantly

elevated and increased adjusted OR [*4, *5, *6]

Increased odds for drivers taking opioids; highest odds were for drivers taking 100-199 MEQ [13]

Increased odds for older female drivers compared to older males [14]

*Three studies used same data sets from previous cell

(n=3) Increased risk using

crude OR [7] Increased IRR [11] No significant increase in

OR [16]

(n=2) Elevated risk for women

(aged 25-55) & men (aged 25-65) [10]

Increased adjusted OR of at least one unsafe driver action for CMV drivers [17]

Systematic Reviews

N/A N/A (n=7) No increased risk [20,

25] Limited evidence [18] Insufficient data [19] Mixed results [22] Increased risk

through meta-analysis [21, 23]

N/A

OR= Odds Ratio; IRR= Incident Rate Ratio; SIR= Standard Incidence Ratio; MEQ= Morphine Equivalent

+Q1a Specific Opioids & Crash Risk

  Codeine MorphineNatural Opium

AlkaloidsMethadone

Original Research Articles

(n= 4) Increased SIR; risk decreased

and was non-significant when co-prescriptions were excluded [1]

Increased IRR when starting prescription and four weeks after [11]

No difference in codeine prevalence between roadside controls and injured drivers [8] or fatally injured drivers [12]

(n=1) No difference in

prevalence between roadside controls and injured drivers [8]

(n=1) Increased crash risk

from national registry database [3]

(n=2) Increased risk of

crash [2] Methadone was

more prevalent in roadside drivers than drivers involved in accidents [8]

Systematic Reviews

N/A N/A N/A (n=1) Increased

involvement in accidents & increased responsibility for accidents [24]

OR= Odds Ratio; IRR= Incident Rate Ratio; SIR= Standard Incidence Ratio

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+Q1a: Stimulants & Crash Risk12

  Amphetamines Methylphenidate

Original Research Articles

(n=5) Increased risk of drivers being involved in an

accident, being seriously injured, and being killed [*4, *5, *6, *7, *8]

*All studies used the same data set

(n=1) Stable use improved self-reported

risky driving in young drivers with ADHD [9]

Systematic Reviews (n=1) Included four relevant articles; only one

showed impairment 23]

N/A

+Q1a Conclusions

There is moderate evidence to support the contention that licit use of opioids increases the risk of a motor vehicle crash.

Several large and recent studies link opioid use to increased risk of driver fatalities, driver injury, crash risk, and unsafe driver actions.

Most identified studies show increased risk. However, many of the findings are drawn from the same large European dataset, and many of them also classify all opioids together. Results for specific opioids are more limited and less convincing.

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+Q1a Conclusions

There is weak evidence to support the contention that licit use of stimulants increases the risk of a motor vehicle crash.

Most of the available evidence pertains to amphetamines and comes from a large European study which showed an increased risk of driver fatalities, driver injury, and crash risk.

The use of stimulants to address driver medical conditions such as ADHD may improve driver crash risk based on one small study. Further research is required.

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Research Question 1bWhat is the relationship between licit use of prescribed Schedule II opioids or stimulants and indirect measures of driver performance?

Evidence base n=29

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+Q1b: Opioids & Indirect Measures

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Opioids

Original Research Articles Systematic Reviews

(n=2) Impairment of driving related skills in chronic

opioid users compared to healthy controls [33]; but no impairment was shown in actual driving [32]

(n=6) Limited evidence [18] No conclusions; insufficient data [19] Some impairment from stable opioid use found in

one-third of studies; strong evidence for no impairment on simulator [20]

Minor cognitive deficits for long-term use; impairment associated with higher doses [47]

Causes some moderate impairment; effects are dependent upon type and dose of opioid [23]

Found two groups of users: new opioid users/recent dose increase (naïve users¹) who are likely to demonstrate impairment; and chronic users who are not impaired by use [25]

¹naive users refers to subjects who are expected to respond differently than chronic drug users due to limited or no prior exposure to the drug

+Q1b: Opioids & Indirect Measures: Original Research

CodeineCodeine/

ParacetamolOxycodone

Oxycodone/Paracetamol

MorphineHydrocodone/

Hydromorphone & Meperidine

Methadone

(n=1) No increased

impairment in reaction time for chronic pain patients [30]

(n=1) No significant

differences between three drug doses and placebo on driving simulator tasks [26]

(n=4) No impairment

in psychomotor skills after 10 mg [35, 36, 37], but one study found significant impairment after 20 mg [36]

Failed to show non-inferiority [28]

(n=1) Three significant

differences were found at low dose (5/325 mg; easy & hard tracking & divided attention task); two differences were found at the high dose (10/650 mg; hard tracking test & divided attention) [38]

(n=1) High dose

morphine group performed significantly worse than low dose morphine group and placebo group; placebo group out-performed both morphine groups [36]

N/A (n=3) No differences

on five tests between peak and trough groups; peak group performed better on some tasks [27]

Methadone maintenance (MM) improved cognitive performance after 3 months [29]

Controls out-performed MM and abstinence group; abstinence group out-performed MM [31]

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+Q1b: Opioids & Indirect Measures:Systematic Reviews

CodeineCodeine/

Paracetamol

OxycodoneOxycodone/Paracetamo

lMorphine

Hydrocodone/ Hydromorpho

ne & Meperidine

Methadone

(n=1) Found

suggestive evidence of impairment [48]

N/A (n=1) Found

suggestive evidence of impairment in attention, divided attention, psychomotor skills, reaction test, and visual functions; a dose effect relationship was shown [48]

N/A

(n=2) Decreased

RT, but no decrease in accuracy [23]

Found evidence of impairment with most impairment related to attention and RT [24]

(n=1) Found

suggestive evidence of impairment; for both drugs, studies found impairment in attention, psychomotor skills, reaction test, and visual functions ; dose-effect relationship was observed for both drugs [48]

(n=1) Impairing

potential in opioid-naïve subjects [24]

RT = Reaction Time

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+Q1b: Stimulants & Indirect Measures

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  Amphetamines Methamphetamine Lisdexamfetamine Methylphenidate

Original Research Articles

(n=4) 10 mg d-amphetamine

improved driving performance; 40 mg improved car-crossing RT; doesn’t compensate for fatigue [41]

Enhanced performance after d-amphetamine [42]

No evidence of impairment; improved perceptual speed & RT [43]

Performed better on simulator, but not significant [44]

(n=1) No evidence of

impairment on simulator tasks; improved performance on various simulator tasks [43]

(n=2) Improved

performance on various tasks in young drivers with ADHD [*39, *40]

*Two studies used same data set

(n=2) Improved

performance on various driving simulator tasks [38, 45]

Systematic Reviews

(n=1) Positive effects and

negative effects observed [23]

(n=1) Positive effects and

negative effects observed [23]

N/A (n=1) Improved driver

performance in adults with ADHD [46]

RT= Reaction time

+Q1b Conclusions

There is moderate evidence that licit use of opioids negatively impacts indirect measures of driver performance.

Studies generally found indicators of impairment, especially for drug-naïve individuals. Impairment was most pronounced on psychomotor vigilance tasks related to pertinent driving skills such as attention, vision, auditory perception, and reaction time.

Fewer studies included driving simulators or roadside driving tests; however, where these tests were included, findings tended not to be significant. Findings vary across drug and dose.

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+Q1b Conclusions

There is weak evidence that licit use of stimulants positively impacts indirect measures of driver performance among drivers with ADHD based on consistent findings among a small number of studies.

The handful of relevant studies generally found that stimulants improve performance among adults with ADHD on psychomotor vigilance tests related to reaction time and complex tasks, as well as performance in a driving simulator related to speeding and weaving.

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+Q1b ConclusionsThere is moderate evidence that licit use of stimulants has minimal or positive indirect measures of driver performance among drivers taking low doses of stimulants.

The handful of relevant studies generally found limited or no negative outcomes and some small improvements in psychomotor vigilance tasks related to reaction time, coherence, car-following, accuracy, and speed. Effects tend to be dose specific, and may only be present for the use of small or moderate doses.

Results were mixed as to whether stimulants can help to counter the effects of sleep deprivation.

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Research Question 2Are the effects of licit use of prescribed opioids or stimulants measureable by serum levels? Do these effects remain consistent or vary based on metabolism or other pharmacokinetic parameters?

Evidence base n=14

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+Q2: Serum Levels

Serum LevelsOriginal Research Articles Systematic Reviews

(n= 10 )

Measuring results via serum levels is largely in concordance with measurements done other ways [8,30,33,36,41,43,44]

Found three additional significant results for codeine using serum levels [26]

(n=4) Serum levels are positively associated with

impairment [19, 23]

One out of three studies reviewed linked blood morphine levels to cognitive deficits [47]

Evidence of concentration relationship for some opioids, but not morphine [48]

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+Q2 ConclusionsThere is moderate evidence that the effects of opioids and stimulants are measureable by serum levels.

Findings were generally consistent across studies that serum levels are comparable to other methods in investigating relationships between licit drug use and driving impairment. However, this relationship likely exists for only certain Schedule II medications, and may also be subject to floor or ceiling effects.

Investigating relationships by serum level allows for a better understanding of possible variation due to differences in how individuals metabolize medicines.

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Research Question 3Do the effects worsen or improve when: 1) drug-drug interactions take place with other Schedule II or over-the-counter medications; or 2) the drug has been chronically administered over a period of time (stable use)?

Evidence base n=19

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+Q3: Stable Use

Stable UseOriginal Research Articles Systematic Reviews

(n=9) No elevated risk [28, 30, 45] Mixed results [32, 33] Impairment, but inconclusive due to potential confounding

factor of medical conditions [31] No significant risk of road trauma among new opioid users

[13] Higher risk of accident for new opioid users than chronic

users , but not significant [16] Increased risk after beginning medication, but risk

decreased over time; time of decrease to non-significance varies among drugs [11]

(n=7) Impairing effect from first-time opioid use [19] Impairment for long-term opioid use [23, 47] No difference in motor vehicle accidents or violations for

stable-use opioid patients; no cognitive or psychomotor impairment [20, 25]

Psychomotor impairment for chronic pain, stable-use morphine patients; no performance difference in stable-use and patients with similar diseases [48]

Increased crash risk for methadone maintained patients; cognitive & psychomotor impairments [24]

No impairment for first-time stimulant use [19] Cognitive & psychomotor impairment with chronic

amphetamine use; impairment correlated with severity or duration of use [23]

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+Q3: Drug Interactions

Drug InteractionsOriginal Research Articles Systematic Reviews

(n=4) No difference in performance for two

doses of codeine/paracetamol compared to placebo [26]

Impairment on tracking test and divided attention task after oxycodone/paracetamol dose [38]

Increased risk of crash for the first four weeks of use of compound analgesic preparations containing acetaminophen and an opioid [11]

Elevated risk across a variety of conditions for drivers fulfilling a prescription for codeine, but dropped to non-significant when co-prescriptions were excluded [1]

(n=1) No conclusions; insufficient data [19]

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+Q3 Conclusions

The evidence pertaining to whether Schedule II opioids and stimulants interact with other Schedule II or prescription medications is unacceptably weak.

Limited data investigates the question of interactions, and what data do exist, conflict. Findings are likely drug and dose specific, and an insufficient evidence base exists at this time to adequately address the question.

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+Q3 Conclusions

There is moderate evidence that stable use of Schedule II opioids is associated with reduced negative impacts.

Consistent data suggest that the negative impacts of opioids on driving and driving related skills diminish over time when doses remain stable. This is not the case for positive impacts, such as those that may be associated with methadone maintenance treatments. However, negative effects of opioids may still remain, even in chronic users.

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+Q3 Conclusions

The evidence pertaining to whether chronic use of stimulants impacts driving or driving related skills is unacceptably weak. A limited evidence base makes it difficult to draw conclusions on this topic.

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Conclusion

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+Overall Conclusions

Moderate evidence to support the contention that licit use of opioids increases the risk of a motor vehicle crash

Weak evidence to support the contention that licit use of stimulants increases the risk of a motor vehicle crash

Moderate evidence that licit use of opioids negatively impacts indirect measures of driver performance

Weak evidence that licit use of stimulants positively impacts indirect measures of driver performance among drivers with ADHD

Moderate evidence that licit use of stimulants has minimal or positive indirect measures of driver performance among drivers taking low doses of stimulants

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+Overall Conclusions

Moderate evidence that the effects of opioids and stimulants are measureable by serum levels

Unacceptably weak evidence of Schedule II opioid and stimulant’s interactions with other Schedule II or prescription medications

Moderate evidence that stable use of Schedule II opioids is associated with reduced negative impacts on driving and driving related skills

Unacceptably weak evidence of chronic use of stimulants’ impact on driving or driving related skills

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