Pharmaceutical Overdose Deaths, United States, 2010

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DOI: 10.1001/jama.2013.272 · Source: PubMed
because smoking cessation is the most effective tool for
risk reduction, be it cancer risk, cardiovascular risk, or
progression of COPD. This potentially makes a negative
outcome of screening counterproductive because it might
be viewed as an incentive to continue smoking. However,
smoking cessation remains difficult in any setting. Adher-
ence is low and the outcome of screening has little long-
term influence on smoking behavior.
1
It recently has been shown that cardiovascular risk in
smokers is increased, and this increase holds for any CAC
score.
2
Whereas the increased risk in smokers might sug-
gest cardiovascular screening is not worthwhile in this
population, the same study showed that mortality still
increases substantially with higher CAC scores, even in
smokers. These findings are corroborated by results from
others,
3
even in the setting of nongated chest CT scans
used for cancer screening.
Although the cardiovascular risk is increased on aver-
age, there is wide variation among smokers, which makes
screening potentially useful to specifically detect those at
high risk. Because smoking and CAC are independent risk
factors, prediction will improve and not worsen when smok-
ing and CAC and non-CAC are combined.
Computed tomography technology currently used for lung
cancer screening is limited by lack of electrocardiography
gating. While this limitation reduces its value for exclud-
ing coronary calcium, the presence of larger amounts of cal-
cium can be reliably detected, and the absolute risk of car-
diovascular disease in individuals with high CAC scoring
on screening scans is increased. Therefore, screening CT
scans can readily establish increased risk. The real ques-
tion is not whether to use the additional information pro-
vided by lung cancer screening but whether a highly posi-
tive result will be able to trigger treatment that can actually
reduce this increased risk.
For osteoporosis, quantitative CT of the lumbar spine
had been superior to DEXA for measuring bone architec-
ture and density.
4
Technical and financial reasons have led
to the widespread use of DEXA and to the decline of CT as
an investigative tool. While osteoporosis assessment is gen-
erally performed on the lumbar spine, the thoracic spine is
also affected and is readily assessable by chest CT. Direct
implementation is hampered by the limited data
5
available
from most individuals, but it is not a reason why CT of the
thoracic spine should not be able to detect osteopenia or
osteoporosis.
Although it is debated as to whether early diagnosis of
COPD is useful, COPD and emphysema are independent
predictors of lung cancer; therefore, detection may aid a
more personalized and cost-effective lung cancer screening
regimen.
Independent of whether or not one supports CT-based
lung cancer screening, extending this screening to other dis-
eases that can be detected early by chest CT will provide
valuable epidemiological data at least. At best, it may con-
tribute to secondary prevention of some of the most debili-
tating diseases in the developed world.
Onno M. Mets, MD, PhD
Pim A. de Jong, MD, PhD
Mathias Prokop, MD, PhD
Author Affiliations: Department of Radiology, University Medical Center Utrecht,
Utrecht, the Netherlands (Drs Mets and de Jong) (pimdejong@gmail.com); and
Department of Radiology, Radboud University Nijmegen Medical Center, Nijme-
gen, the Netherlands (Dr Prokop).
Conflict of Interest Disclosures: The authors have completed and submitted the
ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Prokop reported
receiving grants or having grants pending from Philips Medical Systems and Toshiba
Medical Systems; serving on speakers’ bureaus for Bracco, Toshiba Medical Sys-
tems, Bayer-Schering, CME Science, and Philips Medical Systems; receiving travel
expenses from Toshiba Medical Systems, Philips Medical Systems, European School
of Radiology, and various conferences; and receiving fees for reading a study from
Bracco. Drs Mets and de Jong reported no disclosures.
1. van der Aalst CM, van Klaveren RJ, van den Bergh KA, Willemsen MC, de Koning
HJ. The impact of a lung cancer computed tomography screening result on smok-
ing abstinence. Eur Respir J. 2011;37(6):1466-1473.
2. McEvoy JW, Blaha MJ, Rivera JJ, et al. Mortality rates in smokers and non-
smokers in the presence or absence of coronary artery calcification. JACC Cardio-
vasc Imaging. 2012;5(10):1037-1045.
3. Shemesh J, Henschke CI, Shaham D, et al. Ordinal scoring of coronary artery
calcifications on low-dose CT scans of the chest is predictive of death from car-
diovascular disease. Radiology. 2010;257(2):541-548.
4. Link TM. Osteoporosis imaging: state of the art and advanced imaging. Radiology.
2012;263(1):3-17.
5. Budoff MJ, Hamirani YS, Gao YL, et al. Measurement of thoracic bone mineral
density with quantitative CT. Radiology. 2010;257(2):434-440.
RESEARCH LETTER
Pharmaceutical Overdose Deaths, United States,
2010
To the Editor: Data recently released by the National Cen-
ter for Health Statistics show drug overdose deaths in-
creased for the 11th consecutive year in 2010.
1
Pharmaceu-
ticals, especially opioid analgesics, have driven this increase.
2
Other pharmaceuticals are involved in opioid overdose
deaths, but their involvement is less well characterized. Using
2010 mortality data, we describe the specific drugs in-
volved in pharmaceutical and opioid-related overdose deaths.
Methods. Data are from the National Vital Statistics Sys-
tem multiple cause-of-death file, which is based on death
certificates submitted by medical examiners or coroners.
1
Drug overdose deaths were those assigned an underlying
cause of death using the International Classification of Dis-
eases, Tenth Revision (ICD-10) codes X40-X44 (uninten-
tional), X60-X64 (suicide), X85 (homicide), and Y10-Y14
(undetermined intent). Pharmaceutical-related overdose
deaths were those assigned specific ICD-10 codes T36-
T39, T40.2-T40.4, T41-T43.5, and T43.8-T50.8; psycho-
therapeutic and central nervous system pharmaceuticals were
defined as T40.2-T40.4, T42, T43.0-T43.5, T43.8, T43.9;
and opioid analgesics were those assigned codes T40.2-
T40.4. Pharmaceutical deaths by this definition are pre-
dominately due to prescription drugs; a small minority in-
volve over-the-counter or illicit drugs combined with
prescription drugs in the same ICD-10 T codes. Institu-
LETTERS
©2013 American Medical Association. All rights reserved. JAMA, February 20, 2013—Vol 309, No. 7 657
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tional review board approval was waived because no per-
sonal identifiers were involved.
Results. In 2010, there were 38 329 drug overdose
deaths in the United States; most (22 134; 57.7%) involved
pharmaceuticals; 9429 (24.6%) involved only unspecified
drugs. Of the pharmaceutical-related overdose deaths,
16 451 (74.3%) were unintentional, 3780 (17.1%) were
suicides, and 1868 (8.4%) were of undetermined intent.
Opioids (16 651; 75.2%), benzodiazepines (6497; 29.4%),
antidepressants (3889; 17.6%), and antiepileptic and anti-
parkinsonism drugs (1717; 7.8%) were the pharmaceuti-
cals (alone or in combination with other drugs) most com-
monly involved in pharmaceutical overdose deaths
(T
ABLE). Among overdose deaths involving opioid analge-
sics, the pharmaceuticals most often also involved in these
deaths were benzodiazepines (5017; 30.1%), antidepres-
sants (2239; 13.4%), antiepileptic and antiparkinsonism
drugs (1125; 6.8%), and antipsychotics and neuroleptics
(783; 4.7%).
Opioids were frequently implicated in overdose deaths in-
volving other pharmaceuticals. They were involved in the
majority of deaths involving benzodiazepines (77.2%), an-
tiepileptic and antiparkinsonism drugs (65.5%), antipsy-
chotic and neuroleptic drugs (58.0%), antidepressants
(57.6%), other analgesics, antipyretics, and antirheumatics
(56.5%), and other psychotropic drugs (54.2%). Among over-
dose deaths due to psychotherapeutic and central nervous
system pharmaceuticals, the proportion involving only a
single class of such drugs was highest for opioids (4903/
16 651; 29.4%) and lowest for benzodiazepines (239/6497;
3.7%) (F
IGURE).
Comment. Death certificate data have limitations,
3
but
they are the sole source for detailed death information at
the national level. This analysis is limited by the 25% of death
certificates in which the type of drugs involved was not speci-
fied, an omission due to lack of toxicological testing or fail-
ure to record the results of such tests on the death certifi-
cate. Therefore, the numbers reported in this analysis are
undercounts. Additionally, the degree to which drugs are
specified on death certificates might vary across the United
States and therefor e differentially under count types of drugs
more common in areas in which death certificates are less
complete. This might affect the ranking of some pharma-
ceuticals in the Table.
Table. Specific Drug Involvement in Pharmaceutical Overdose Deaths, United States, 2010
Drug or Drug Class
No. (%)
a
Opioid Analgesic
Involvement in Deaths
for Specific Drugs,
No./Total (%)
Drug Involvement
in Pharmaceutical
Overdose Deaths
Specific Drug Involvement
in Opioid Analgesic–Related
Overdose Deaths
All pharmaceuticals (T36-T39, T40.2-T40.4, T41-T43.5,
T43.8-T50.8)
22 134 (100.0) NA 16 651/22 134 (75.2)
Opioid analgesics (T40.2-T40.4) 16 651 (75.2) 16 651 (100.0) 16 651/16 651 (100.0)
Benzodiazepines (T42.4) 6497 (29.4) 5017 (30.1) 5017/6497 (77.2)
Antidepressants (T43.0-T43.2) 3889 (17.6) 2239 (13.4) 2239/3889 (57.6)
Antiepileptic and antiparkinsonism drugs (T42.0-T42.2,
T42.5-T42.8)
1717 (7.8) 1125 (6.8) 1125/1717 (65.5)
Systemic and hematological drugs (T45) 1591 (7.2) 699 (4.2) 699/1591 (43.9)
Antipsychotic and neuroleptic drugs (T43.3-T43.5) 1351 (6.1) 783 (4.7) 783/1351 (58.0)
Acetaminophen (T39.1) 881 (4.0) 405 (2.4) 405/881 (46.0)
Respiratory drugs (T48.3-T48.7) 487 (2.2) 143 (0.9) 143/487 (29.4)
Cardiovascular drugs (T46) 354 (1.6) 57 (0.3) 57/354 (16.1)
Barbiturates (T42.3) 296 (1.3) 148 (0.9) 148/296 (50.0)
Autonomic nervous system drugs (T44) 263 (1.2) 110 (0.7) 110/263 (41.8)
Nonsteroidal anti-inflammatory drugs (T39.0, T39.2, T39.3) 228 (1.0) 53 (0.3) 53/228 (23.2)
Anesthetics and therapeutic gases (T41) 195 (0.9) 49 (0.3) 49/195 (25.1)
Hormones, insulins, glucocorticoids (T38) 147 (0.7) 10 (0.1) 10/147 (6.8)
Anti-infectives (T36-T37) 114 (0.5) 44 (0.3) 44/114 (38.6)
Diuretics and other drugs, medicaments, and biological
substances (T50.0-T50.8)
56 (0.3) 27 (0.2) 27/56 (48.2)
Topical drugs (T49) 34 (0.2) 6 (0.04) 6/34 (17.6)
Other psychotropic drugs (T43.8, T43.9) 24 (0.1) 13 (0.1) 13/24 (54.2)
Muscle relaxants (T48.0-T48.2) 24 (0.1) 4 (0.02) 4/24 (16.7)
Other analgesics, antipyretics, antirheumatics (T39.4,
T39.8, T39.9)
23 (0.1) 13 (0.1) 13/23 (56.5)
Gastrointestinal drugs (T47) 6 (0.03) 2 (0.01) 2/6 (33.3)
Abbreviation: NA, data not applicable.
a
Deaths are not mutually exclusive. Deaths involving more than 1 drug or drug class are counted multiple times.
LETTERS
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This analysis confirms the predominant role opioid
analgesics play in pharmaceutical overdose deaths, either
alone or in combination with other drugs. It also, however,
highlights the frequent involvement of drugs typically pre-
scribed for mental health conditions such as benzodiaz-
epines, antidepressants, and antipsychotics in overdose
deaths. People with mental health disorders are at
increased risk for heavy therapeutic use, nonmedical use,
and overdose of opioids.
4-6
Screening, identification, and
appropriate management of such disorders is an important
part of both behavioral health and chronic pain manage-
ment. Tools such as prescription drug monitoring pro-
grams and electronic health records can help clinicians to
identify risky medication use and inform treatment deci-
sions, especially for opioids and benzodiazepines.
Christopher M. Jones, PharmD
Karin A. Mack, PhD
Leonard J. Paulozzi, MD
Author Affiliations: Centers for Disease Control and Prevention, National Center
for Injury Prevention and Control, Atlanta, Georgia (fjr0@cdc.gov).
Author Contributions: Dr Jones had full access to all of the data in the study and
takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Jones, Paulozzi.
Acquisition of data: Jones.
Analysis and interpretation of data: Jones, Mack, Paulozzi.
Drafting of the manuscript: Jones.
Critical revision of the manuscript for important intellectual content: Jones, Mack,
Paulozzi.
Statistical analysis: Jones.
Administrative, technical, or material support: Mack, Paulozzi.
Study supervision: Jones.
Conflict of Interest: The authors have completed and submitted the ICMJE Form
for Disclosure of Potential Conflicts of Interest and none were reported.
Funding/Support: The US Centers for Disease Control and Prevention funded this
study.
Role of the Sponsor: The US Centers for Disease Control and Prevention sup-
ported the staff responsible for the design and conduct of the study; in the col-
lection, analysis, and interpretation of the data; or in the preparation, review, or
approval of the manuscript.
Disclaimer: The views expressed in this article are those of the authors and do not
necessarily reflect the official position of the US Centers for Disease Control and
Prevention.
1. Centers for Disease Control and Prevention. National Vital Statistics System.
2010 Multiple Cause of Death File. Hyattsville, MD: US Department of Health
and Human Services, Centers for Disease Control and Prevention; 2012.
2. Paulozzi LJ, Jones C, Mack K, Rudd R; Centers for Disease Control and Pre-
vention (CDC). Vital signs: overdoses of prescription opioid pain relievers—
United States, 1999-2008. MMWR Morb Mortal Wkly Rep. 2011;60(43):
1487-1492.
3. Wysowski DK. Surveillance of prescription drug-related mortality using death
certificate data. Drug Saf. 2007;30(6):533-540.
4. Edlund MJ, Martin BC, Fan MY, Braden JB, Devries A, Sullivan MD. An analy-
sis of heavy utilizers of opioids for chronic noncancer pain in the TROUP study.
J Pain Symptom Manage. 2010;40(2):279-289.
5. Becker WC, Sullivan LE, Tetrault JM, Desai RA, Fiellin DA. Non-medical use,
abuse and dependence on prescription opioids among US adults: psychiatric, medi-
cal and substance use correlates. Drug Alcohol Depend. 2008;94(1-3):38-
47.
6. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescrib-
ing patterns and opioid overdose-related deaths. JAMA. 2011;305(13):1315-
1321.
Figure. Percentage of Overdose Deaths for Specific Psychotherapeutic and Central Nervous System (CNS) Pharmaceuticals That Involved Only
a Single Drug Class, United States, 2010
35
20
25
30
15
10
5
0
Opioid Analgesics
(n
=
16
651)
Antiepileptic and
Antiparkinsonism
Drugs (n
=
1717)
Benzodiazepines
(n
=
6497)
Barbiturates
(n
=
296)
Antidepressants
(n
=
3889)
Antipsychotic
and Neuroleptic
Drugs (n
=
1351)
Other
Psychotropic
Drugs (n
=
24)
Psychotherapeutic and
CNS Pharmaceuticals, %
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    • "While opioids are the most common class of scheduled medications involved in deaths related to pharmaceutical overdose (75.2 %), benzodiazepines are involved in nearly a third of these overdoses (29.4 %). Additionally, the combination of opioids and benzodiazepines is especially dangerous, with opioids implicated in 77.2 % of deaths involving benzodiazepines , making these two classes of drugs the target of many interventions [2]. Nearly 15,000 people in the United States die from prescription painkiller overdoses every year [3] . "
    [Show abstract] [Hide abstract] ABSTRACT: Background Prescription narcotic overdoses and abuse have reached alarming numbers. To address this epidemic, integrated clinical decision support within the electronic medical record (EMR) to impact prescribing behavior was developed and tested. MethodsA multidisciplinary Expert Panel identified risk factors for misuse, abuse, or diversion of opioids or benzodiazepines through literature reviews and consensus building for inclusion in a rule within the EMR. We ran the rule “silently” to test the rule and collect baseline data. ResultsFive criteria were programmed to trigger the alert; based on data collected during a “silent” phase, thresholds for triggers were modified. The alert would have fired in 21.75 % of prescribing encounters (1.30 % of all encounters; n = 9998), suggesting the alert will have a low prescriber burden yet capture a significant number of at-risk patients. Conclusions While the use of the EMR to provide clinical decision support is not new, utilizing it to develop and test an intervention is novel. We successfully built an alert system to address narcotic prescribing by providing critical, objective information at the point of care. The silent phase data were useful to appropriately tune the alert and obtain support for widespread implementation. Future healthcare initiatives can utilize similar methodology to collect data prospectively via the electronic medical record to inform the development, delivery, and evaluation of interventions.
    Full-text · Article · Dec 2016
    • "Deaths involving sedatives, especially benzodiazepines, have grown even faster in percentage terms, and involvement of these drugs and of psychotropic medications is particularly severely understated on death certificates. Attention has been paid to the role of non-opioids and to combination drug use, but a better understanding is needed since opioids and benzodiazepines are often combined, with greater resulting health risks than the use of either alone [2, 8, 33, 34]. In a more general sense, comprehensive efforts to reduce drug fatalities should account for potential therapeutic benefits and substitution between drugs, the frequency of combination drug use, and the heterogeneity in levels and growth of drug mortality across geographic areas and demographic groups [2, 35, 36]. "
    [Show abstract] [Hide abstract] ABSTRACT: Drug poisoning mortality in the US has risen rapidly but the drugs involved are frequently unspecified on death certificates. Reported and adjusted proportions of specific drug types involved in fatal drug poisonings were calculated using vital statistics mortality data from 1999 to 2012. The adjusted proportions were those predicted to occur if at least one specific type of drug had been identified on the death certificates of all poisoning fatalities. Adjusted involvement rates of opioid analgesic mentions in 2012 were 54.3 % (95 % confidence interval [CI]: 53.6 %–55 %), 40.8 % higher than the reported 38.6 % rate. Adjusted rates for all narcotics, other narcotics, sedatives, or psychotropics, and multiple drug use were 81.5 % (95 % CI: 80.9 %–82.2 %), 38.4 % (95 % CI: 37.8 %–39 %), 30 % (95 % CI: 29.4 %–30.7 %), 26 % (95 % CI: 25.4 %–26.6 %) and 42.8 % (95 % CI: 42.1 %–43.5 %) in 2012, compared to reported proportions of 60.7, 27.9, 18.7, 18 and 26.9 %. The adjustments typically had similar or slightly smaller effects on the estimates in 1999, and larger impacts on subcategories of drug types such benzodiazepines and antipsychotic medications. Based on the adjusted proportions, 22,534, 15,933, 12,457, 10,798, and 17,670 drug deaths in 2012 were estimated to involve opioid analgesics, other narcotics, sedatives, psychotropic medications, and drug combinations, compared to death certificate reports of 16,007, 11,567, 7,754, 7,467, and 11,176. Death certificates substantially understate the involvement of opioid analgesics, sedatives, psychotropics, and drug combinations in fatal drug poisonings. Adjustment procedures that account for cases where only unspecified drugs are reported on death certificates provide more accurate information.
    Full-text · Article · Dec 2016
    • "Abuse of prescription opioids has been cited as the fastest growing drug problem in the United States [1], and has surpassed use of cocaine and heroin combined as the cause of mortality [2,3]. In 2013, nearly two million Americans abused prescription opioids and 16,235 deaths were attributed to prescription opioids representing almost a fourfold increase since 1999 [4,5,6]. In an attempt to curb this public health problem and reduce prescription of opioids to 'drug-seekers', numerous state and hospital opioid prescription guidelines have been developed and disseminated [7,8]. "
    [Show abstract] [Hide abstract] ABSTRACT: Prescription drug abuse is a growing problem nationally. In an effort to curb this problem, emergency physicians might rely on subjective cues such as race-ethnicity, often unknowingly, when prescribing opioids for pain-related complaints, especially for conditions that are often associated with drug-seeking behavior. Previous studies that examined racial-ethnic disparities in opioid dispensing at emergency departments (EDs) did not differentiate between prescriptions at discharge and drug administration in the ED. We examined racial-ethnic disparities in opioid prescription at ED visits for pain-related complaints often associated with drug-seeking behavior and contrasted them with conditions objectively associated with pain. We hypothesized a priori that racial-ethnic disparities will be present among opioid prescriptions for conditions associated with non-medical use, but not for objective pain-related conditions. Using data from the National Hospital Ambulatory Medical Care Survey for 5 years (2007–2011), the odds of opioid prescription during ED visits made by non-elderly adults aged 18–65 for ‘non-definitive’ conditions (toothache, back pain and abdominal pain) or ‘definitive’ conditions (long-bone fracture and kidney stones) were modeled. Opioid prescription at discharge and opioid administration at the ED were the primary outcomes. We found significant racial-ethnic disparities, with non-Hispanic Blacks being less likely (adjusted odds ratio ranging from 0.56–0.67, p-value < 0.05) to receive opioid prescription at discharge during ED visits for back pain and abdominal pain, but not for toothache, fractures and kidney stones, compared to non-Hispanic whites after adjusting for other covariates. Differential prescription of opioids by race-ethnicity could lead to widening of existing disparities in health, and may have implications for disproportionate burden of opioid abuse among whites. The findings have important implications for medical provider education to include sensitization exercises towards their inherent biases, to enable them to consciously avoid these biases from defining their practice behavior.
    Full-text · Article · Aug 2016
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