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Weight Loss Achieved with Medication Can Delay Onset of
Type 2 Diabetes in At-Risk Individuals
Garvey WT, Ryan DH, Henry R, et al. Prevention of type 2 diabetes in subjects with prediabetes and metabolic
syndrome treated with phentermine and topiramate extended release. Diabetes Care 2014;37:912–21.
Study Overview
Objective. To determine the effect of phentermine and
topiramate extended release (PHEN/TPM ER) treatment on progression to type 2 diabetes and/or cardiometabolic disease in subjects with prediabetes and/or
metabolic syndrome (MetS) at baseline.
Design. Sub-group analysis of a larger double-blind, randomized, placebo-controlled trial of PHEN/TPM ER in
overweight and obese adults.
Setting and participants. The larger study had 2 phases
—a 56-week weight loss trial (CONQUER, n = 866),
followed by an extension of the drug trial out to 108
weeks (SEQUEL, n = 675) in a sub-group of CONQUER
participants. The CONQUER trial, based at 93 U.S. centers, enrolled overweight or obese patients with at least 2
obesity-related comorbidities and randomly assigned them
to receive either placebo or PHEN/TPM ER at a lower
(7.5 mg/46 mg) or higher (15 mg/92 mg) daily dose.
All 3 groups also received lifestyle modification counseling that included an evidence-based diet and exercise
curriculum. Participants received study drug and lifestyle
counseling in the setting of monthly visits during the 60(CONQUER) or 108-week (SEQUEL) follow-up period.
The analyses presented in this paper focus on the
475 participants who completed both CONQUER and
SEQUEL and who were characterized as pre-diabetic or
as having the metabolic syndrome (MetS) at baseline.
Pre-diabetes was defined as having a blood glucose level
of 100–125 mg/dL or higher while fasting, or 140–199
mg/dL after an oral glucose tolerance test (GTT). MetS
was characterized in participants who displayed 3 or
more of the following at baseline: waist circumference
≥ 102 cm in men or 88 cm in women; triglycerides
≥ 150 mg/dL or on a lipid-lowering medication; HDL
< 40 mg/dL in men or < 50 mg/dL in women; systolic
BP ≥ 130 mm Hg or diastolic BP ≥ 85 mm Hg (or on
antihypertensive); and fasting glucose ≥ 100 mg/dL or
on treatment for elevated glucose.
Main outcome measures. The primary outcome for this
study was percent weight loss at 108 weeks of follow-up
(or early termination). Secondary outcomes included
cardiometabolic changes, such as development of type 2
diabetes and changes in lipid measures, blood pressure,
and waist circumference. These were assessed at baseline,
week 56, and week 108 (or at early termination). Rates
of progression to type 2 diabetes were compared between
the treatment groups using chi-square testing. Intention-
Outcomes Research in Review Section Editors
Jason P. Block, MD, MPH
Brigham and Women’s Hospital
Boston, MA
Melanie Jay, MD, MS
NYU School of Medicine
New York, NY
Kristina Lewis, MD, MPH
Kaiser Permanente Center for
Health Research
Atlanta, GA
William Hung, MD, MPH
Mount Sinai School of Medicine
New York, NY
Gordon Ngai, MD, MPH
Mount Sinai School of Medicine
New York, NY
Allison Squires, PhD, RN
NYU College of Nursing
New York, NY
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Vol. 21, No. 9 September 2014 JCOM 393
OUTCOMES RESEARCH IN REVIEW
to-treat (ITT) ANCOVA analysis was performed with
multiple imputation techniques to address missing data,
as well as with an alternative analysis using last observation carried forward.
Results. The study arms were similar with respect to
baseline characteristics. Average age was 51 years in the
high dose PHEN/TPM ER arm and 52 in the other
arms. Over half (65%) of participants were women
and 86% were Caucasian. Mean BMI was 36 kg/m2
(class II obesity). Over half of participants were on
antihypertensive medications at baseline but with wellcontrolled blood pressure (mean 128/80 mm Hg).
Of the 475 people in this analysis, 316 met criteria for
prediabetes, 451 for MetS, and 292 for both prediabetes
and MetS.
Weight loss at 2 years was significantly greater in
subjects taking PHEN/TPM ER (10.9% in the lower
dose group, 12.1% in the higher dose group) compared
to those taking placebo (2.5%) (P < 0.001). Mirroring weight loss results, type 2 diabetes incidence was
also significantly lower in the drug treatment arms
than in the placebo arm at 2 years after randomization—annualized incidence was 6.1% for placebo vs.
1.8% for lower-dose drug and 1.3% for higher-dose drug
(P < 0.05). Greater weight loss was associated with
greater decrease in diabetes incidence across all 3 arms of
the study. Those persons who did not achieve at least a
5% weight loss at 2 years had the highest annualized risk
of developing diabetes (6.3%), compared with a 0.9% risk
among those who lost at least 15% of their weight. Improvements in other cardiometabolic parameters, including HDL, triglycerides, waist circumference, and insulin
sensitivity index, was more common among the PHEN/
TPM ER participants compared with placebo. Blood
pressure decreased slightly for all 3 groups and there was
no significant difference between the drug arms and the
placebo arm.
Discontinuation of study medication occurred in all 3
groups (3.1% in placebo, 6.1% in lower-dose medication,
and 5.5% in higher-dose medication), with serious adverse
events in 5%, 7%, and 8.5%, respectively. There were no
deaths.
Conclusion. PHEN/TPM ER administered over a 2-year
period significantly improved weight loss and decreased
progression to type 2 diabetes relative to placebo in a
group of at-risk participants.
394 JCOM September 2014 Vol. 21, No. 9
Commentary
Diabetes and related cardiometabolic disease are major
contributors to morbidity and mortality in adults. With
the exception of invasive treatments such as bariatric surgery, reversal of diabetes once it is established has proven
quite difficult [1,2], and thus there is an increased emphasis from the public health and medical communities
on preventing the development of this disease in the
first place. Complicating the picture, recently broadened
criteria for pre-diabetes will likely result in a very large
number of these at-risk individuals being identified [3,4].
Although intensive lifestyle interventions resulting in
a 5% to 7% weight loss among pre-diabetics have been
shown to delay progression to diabetes [5], the translation of these programs into real-world settings has,
so far, shown less promise than the original randomized trials might have indicated [4]. Although there is
ongoing work to try to improve results and uptake in
community-based lifestyle intervention programs, for
many patients and clinicians these resource-intensive
programs currently prove difficult to do well on a
large scale.
Alternative methods of helping patients achieve and
maintain that critical > 5% weight loss are desperately
needed, not only for preventing diabetes, but also for
impacting the numerous other risks associated with
obesity. This particular trial capitalized on the notion
that it is probably successful weight loss, not the intervention format used to achieve that weight loss, which
drives decreased diabetes risk. This study was a subanalysis of a larger randomized trial, and many of the
strengths of that larger study are therefore reflected in
this paper. Participants and study staff were blinded to
treatment arm with the use of placebo, a very important
strength when adverse reactions and drug intolerances
need to be measured. Furthermore, this likely equalized
motivation to comply with the lifestyle recommendations across the treatment arms—this might not have
been the case if patients were aware that they were or
were not receiving study drug. Another key strength of
the study is its duration. PHEN/TPM ER is unique
in that it is approved by the FDA for long-term use.
Whereas many studies of weight loss show maximum
intervention effect at about 6 months followed by
weight regain, this study showed sustained weight loss
up to 2 years after starting therapy, presumably because
participants could actually continue the therapy for the
full 2 years. Most importantly, the intervention itself
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(medication plus low-intensity lifestyle counseling) is
likely highly replicable in clinical practice.
There are some important limitations to consider
when interpreting the results from this study. First,
the participants analyzed in this paper were comprised
entirely of people who had already participated in a full
year of the parent study and therefore probably represent a sub-group that might have been experiencing
greater success as a result of their participation, potentially generating an overly optimistic estimate of weight
loss and health effect for all of the groups relative to
what might be seen in a general population. This feature
of the design also limits this study’s ability to comment
on drug intolerance or early adverse reactions—those
who didn’t stick with the pills for at least a year would
not have been included in these analyses. In terms of
generalizability, although the infrastructure required
from a clinical standpoint is much lower for an intervention like this (prescribing a medication) compared to
an intensive lifestyle intervention, these drugs are still
costly, and many insurers/providers may not offer them
on formulary. Thus, to realize the long-term benefits
of sustained weight loss, patients may need to face significant out-of-pocket costs, which may limit uptake of
this therapy to those with financial means. For this and
other reasons, it will be important to do future studies
looking at how quickly weight is re-gained once people
stop taking the medication. Another threat to generalizability is the racial makeup of the participants—
the vast majority of them were non-Hispanic white.
Furthermore, although a majority of the participants
had hypertension, it was well-controlled in all (a prerequisite for taking the medication), and it is unclear
whether in a real-world patient population hypertension
would be adequately controlled in a large number of
patients.
Another issue to consider when looking at the use
of weight loss medications for prevention of diabetes is
the relative risk of prolonged medication use compared
with the risk for developing diabetes. Clearly, for obese
patients who are interested in losing weight for other
reasons, prevention of diabetes is a wonderful side effect of achieving that goal. However, it is worth noting
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that even in the highest-risk group of participants in
this study (those who lost < 5% of weight), the annualized risk of developing diabetes was about 6% (< 20%
cumulative risk projected over 3 years). Compare this
to the 7% to 8% serious adverse event rate observed in
those on drug therapy. Although the medication did
reduce annualized diabetes risk significantly, the vast
majority of people in all the arms did not develop diabetes during follow-up. This drives home the point that
our current categorization of pre-diabetes is far from
perfect in identifying people who are at imminent risk
of becoming diabetic, and reinforces the notion that any
treatment we provide to them in the name of diabetes
prevention should be free from risk of harm. Rather
than applying a long-term medication with potentially
harmful side effects to a large group of at-risk patients,
more research is needed to provide tools for clinicians to
think carefully about which of their patients are truly at
highest risk of going on to develop diabetes in the near
future.
Applications for Clinical Practice
Although clinicians ought not use PHEN/TPM ER
exclusively for diabetes prevention based on the results
from this trial, delay of diabetes onset is a possible and
important benefit of the use of PHEN/TPM ER in
obese patients, provided that they are willing to also
make and sustain lifestyle changes in order to lose a clinically significant amount of weight.
—Kristina Lewis, MD, MPH
References
1. Gregg EW, Chen H, Wagenknecht LE, et al. Association of
an intensive lifestyle intervention with remission of type 2
diabetes. JAMA 2012;308:2489-96.
2. Arterburn DE, O’Connor PJ. A look ahead at the future of
diabetes prevention and treatment. JAMA 2012;308:2517–8.
3. Yudkin JS, Montori VM. The epidemic of pre-diabetes: the
medicine and the politics. BMJ. 2014;349:g4485.
4. Kahn R, Davidson MB. The reality of type 2 diabetes prevention. Diabetes care 2014;37:943-9.
5. Knowler WC, Fowler SE, Hamman RF, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:
1677–86.
Vol. 21, No. 9 September 2014 JCOM 395
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Frailty as a Predictive Factor in Geriatric Trauma Patient Outcomes
Joseph B, Pandit V, Zangbar B, et al. Superiority of frailty over age in predicting outcomes among geriatric
trauma patients: a prospective analysis. JAMA Surg. 2014 Jun 11.
Study Overview
Objective. To evaluate the usefulness of the Frailty Index
(FI) as a prognostic indicator of adverse outcomes in geriatric trauma patients.
Design. Prospective cohort study.
Setting and participants. Geriatric (aged 65 and over)
trauma patients admitted to inpatient units at a Level 1
trauma center in Arizona were enrolled. Patients were
excluded if they were intubated/nonresponsive with no
family members present or transferred from another institution (eg, skilled nursing facility). The following categories of data were collected: (a) patient demographics,
(b) type and mechanism of injury, (c) vital signs (eg,
Glasgow coma scale score, systolic blood pressure, heart
rate, body temperature), (d) need for operative intervention,
(e) in-hospital complications, (f) hospital and intensive care
unit (ICU) lengths of stay, and (g) discharge disposition.
Patients or, in the case of nonresponsive patients,
their closest relative, responded to the 50-item Frailty
Index questionnaire, which includes questions regarding
age, comorbid conditions, medications, activities of daily
living (ADLs), social activities, mood, and nutrition. FI
score ranges from 0 (non-frail) to 1 (frail), with an FI of
0.25 or more indicative of frailty based on established
guidelines. Patients were categorized as frail or non-frail
according to their FI scores and were followed during the
course of their hospitalization.
Main outcome measure. The primary outcome measure
was in-hospital complications. In-hospital complications
included myocardial infarction, cardiopulmonary arrest,
pneumonia, pulmonary embolism, sepsis, urinary tract
infection, deep venous thrombosis, disseminated intravascular coagulation, renal insufficiency, and reoperation.
The secondary outcome measure was adverse discharge
disposition, which was defined as death during the
course of hospitalization or discharge to a skilled nursing
facility.
396 JCOM September 2014 Vol. 21, No. 9
Main results. The sample consisted of 250 patients with
a mean age of 77.9 years. Among these, 44.0% were considered frail. Patients with frailty were more likely to have
a higher Injury Severity Score (P = 0.04) and a higher
mean FI (P = 0.01) than those without frailty. There
were no statistically significant differences with respect to
age (P = 0.21), mechanism of injury (P = 0.09), systolic
blood pressure (P = 0.30), or Glasgow Coma Scale score
(P = 0.91) between the groups.
Patients with frailty were more likely to develop
in-hospital complications (37.3% vs 21.4%, P = 0.001)
than those without frailty. Among these complications,
pneumonia and urinary tract infection were the most
common. There were no differences in the rate of reoperation (P = 0.54) between the 2 groups. An FI of
0.25 or higher was associated with the development of
in-hospital complications (P = 0.001) even after adjusting for age, systolic blood pressure, heart rate, and
Injury Severity Score.
Frail patients had longer hospital length of stay
(P = 0.01) and ICU length of stay (P = 0.01),
and were more likely to have adverse discharge disposition (37.3% vs. 12.9%, P = 0.001). All patients who
died during the course of hospitalization (n = 5) were
considered frail. Frailty was also found to be a predictor of adverse discharge disposition (P = 0.001) after
adjustment for age, male sex, Injury Severity Score, and
mechanism of injury.
Conclusion. The FI is effective in identifying geriatric
trauma patients who are vulnerable to poor health outcomes.
Commentary
The diagnosis and treatment of elderly patients is complicated by the presence of multiple geriatric syndromes,
including frailty [1]. Frailty is defined as increased vulnerability to negative health outcomes, marked by physical
and functional decline, that eventually leads to disability, dependency, and mortality [2]. Factors such as age,
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malnutrition, and disease give way to dysregulations of
bodily systems that eventually lead to reductions in mobility, strength, and cognition in frail older adults [3]. In
turn, frail patients, who lack the physiological reserves to
withstand illness and adapt to stressors, experience high
incidences of hospitalizations, mortality, and reduced quality of life. Unsurprisingly, mortality rates among geriatric
trauma patients are higher than those found in ordinary
adult trauma patients [4]. It is, therefore, essential to identify patients with frailty at the outset of hospitalization in
order to improve health outcomes and reduce mortality
rates in this population. Yet, there is a dearth of assessment
tools to predict outcomes in frail trauma patients [5].
This study has several strengths. Outcome measures
are plainly stated. The inclusion criteria was broad enough
to include most geriatric trauma patients, but the authors
eliminated a number of confounders by excluding patients
admitted from institutional settings, who may have been
more susceptible to negative health outcomes at baseline
than noninstitutionalized adults. Recruitment strategies
were acceptable and reflect ethical standards. Groups were
defined based on an accepted and previously validated
FI cutoff. Lack of blinding did not threaten the study’s
design given that most outcomes were beyond the control
of study participants. Multivariate regression adjusted for
a number of potential confounders including age, length
of hospitalization, and injury severity. The Injury Severity Score, the Abbreviated Injury Scale score, and the
Glasgow Coma Scale score are validated instruments that
are widely used and enable standardized assessments of
cognition and degree of injury.
The study methodology also possesses a number of
weaknesses. The authors followed patients from admission to discharge; however, they did not re-evaluate patients following their release from the inpatient setting.
It is, therefore, not clear whether the FI is predictive of
quality of life, functional status, or hospital readmissions upon discharge into the community. The cohort
was largely male (69.2%) and predominately Caucasian.
Participants were recruited from only one medical center. All of these limit the study’s generalizability. In ad-
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dition, the authors do not clarify how they came to define the criteria for in-hospital complications or adverse
discharge disposition. For example, the study does not
consider skin breakdown, a common concern among
older patients who are hospitalized, as an in-hospital
complication. In addition, the authors did not adjust for
the number of diagnoses at baseline or the presence of
chronic comorbid conditions, which are also associated
with negative health outcomes.
Applications for Clinical Practice
Although lengthy, with over 50 variables in 5 categories,
the FI has the potential to help health care providers improve risk stratification, assess patient acuity, and formulate treatment plans to improve the health of frail elderly
patients. The FI will enable hospitals to direct appropriate resources, including staff, to the most vulnerable subsets of patients in order to improve outcomes and reduce
costs. Moreover, awareness of frailty enables greater discussion between patients and families of trauma patients
about the risks and benefits of complex intervention,
increases referrals to palliative care, and improves quality
of life in this population [6].
—Tina Sadarangani, MSN, APRN, and Allison Squires, PhD, RN,
New York University College of Nursing
References
1. Rich MW. Heart failure in the oldest patients: the impact
of comorbid conditions. Am J Geriatr Cardiol 2005;14:
134–41.
2. Fried LP, Ferrucci L, Darer J, et al. Untangling the concepts of disability, frailty, and comorbidity: implications for
improved targeting and care. J Gerontol A Biol Sci Med Sci
2004;59:255–63.
3. Lang PO, Michel JP, Zekry D. Frailty syndrome: a transitional
state in a dynamic process. Gerontology 2009;55:539–49.
4. Hashmi A, Ibrahim-Zada I, Rhee P, et al. Predictors of mortality in geriatric trauma patients: a systematic review and
meta-analysis. J Trauma Acute Care Surg 2014;76:894–901.
5. American College of Surgeons Trauma Quality Improvement
Program. ACS TQIP geriatric trauma management guidelines. Available at https://mtqip.org/docs/.
6. Koller K, Rockwood K. Frailty in older adults: implications for
end-of-life care. Cleve Clin J Med 2013;80:168–74.
Vol. 21, No. 9 September 2014 JCOM 397
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Effect of Substituting Nurses for Doctors in Primary Care
Martínez-González NA, Djalali S, Tandjung R, et al. Substitution of physicians by nurses in primary care: a
systematic review and meta-analysis. BMC Health Serv Res 2014;14:214.
Study Overview
Objective. To investigate the clinical effectiveness and
costs of nurses working as substitutes for physicians in
primary care.
Design. Systematic review and meta-analysis of published
randomized controlled trials (RCTs) and 2 economic
studies that compared nurse-led care with care by primary care physicians on numerous variables, including
satisfaction, hospital admission, mortality, and costs of
health care.
Settings and participants. The 24 RCTs were drawn
from 5 different countries (UK, Netherlands, USA,
Russia, and South Africa). In total, there were 38, 974
participants. Eleven of the studies had less than 200
participants and 13 studies had more than 200 (median,
1624). Mean age was reported in 20 trials and ranged
from 10 to 83 years.
Analysis. The authors assessed risk of bias in the studies,
calculated the study-specific and pooled relative risks
(RR) or standardized mean differences (SMD), and performed fixed-effects meta-analyses.
Main results. Nurse-led care was effective at reducing
the overall risk of hospital admission (RR 0.76, 95% CI
0.64–0.91) and mortality (RR 0.89, 95% CI 0.84–0.96)
in RCTs of ongoing or non-urgent care, longer (at least
12 months) follow-up episodes, and in in larger (n > 200)
RCTs. Pooled analysis showed higher overall scores of
patient satisfaction with nurse led care (SMD 0.18, 95%
Cl 0.13–0.23). Higher-quality RCTs (with better allocation concealment and less attrition) showed higher rates
of hospital admissions and mortality with nurse-led care,
but the difference was not significant. Subgroup analysis
showed that RNs had a stronger effect than nurse practitioners (NPs) on patient satisfaction. The results of costeffectiveness and improved quality of care analysis with
nurses were inconclusive.
398 JCOM September 2014 Vol. 21, No. 9
Conclusion. Nurse-led care appears to have a positive
effect on patient care and outcomes but more rigorous
research is needed to confirm these findings.
Commentary
As the backbone of health care systems around the world,
primary care is facing numerous challenges threatening
patient access to care. Aging populations, economically
strapped governments, and an increasing non-communicable disease burden in developing countries are pushing
global health systems to their capacity. In addition, the
World Health Organization has highlighted the increasing health worker shortage which further limits the capabilities of health systems [1,2]. One proposed solution to
addressing physician shortages is using NPs. Recent studies have shown patient satisfaction, physical, emotional,
and social function, and other outcomes associated with
nurse-led care to be similar to if not better than those
associated achieved by physicians [3–5].
The current meta-analysis has some weaknesses. For
example, 13 of the 24 studies had attrition rates of at
least 20% and only 10 trials had a sufficient sample size
to achieve adequate power in at least 1 outcome, making
it more difficult to identify true differences between control and intervention groups. The sample of RCTs were
heterogeneous in terms of settings, tasks, and reporting
of outcomes. Also, study heterogeneity increased the
difficulty of data synthesis and limited the amount of
information on cost-effective nursing care and quality of
care of patients.
In many of the studies, quality of life among patients
was measured inconsistently, using various disease specific and generic scales, making it difficult to compare
and provide comprehensive results. Additionally, less
than 50% of the patient satisfaction scales used validated
questionnaires.
Results should be interpreted with caution as the
studies were compiled from 5 different countries. The
scope of nursing practice differs in each country and
the different cadres of nurses (RN vs NP vs licensed
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practical nurse [LPN]) also have varying responsibilities.
Cross comparisons between RN/LPN, NP/physician,
and RN/NP need to consider the country context,
regulating bodies, and government policies that dictate
the capabilities and practice of each of these licensed
professionals.
There was a dearth of economic information. Generally, direct costs such as consultations and cases involving patients less than 65 year of age were lower with
nurse-led care, but in other studies costs of nurse-led and
physician-led care were not significantly different.
Applications for Clinical Practice
As the health worker shortage continues, health care facilities will have to decide on the appropriate skill mix to
provide the best patient outcomes while maximizing cost
benefit. While this systematic review and meta-analysis is
promising in supporting nursing-led primary care, more
research is needed, including longer-term studies with
larger sample sizes and more extensive assessment of cost
and quality of life. The use of validated and standardized
instruments to measure patient satisfaction and quality of
care will increase study quality and rigor.
—Melissa T. Martelly, MA, BSN, RN, PCCN, and
Allison Squires, PhD, New York University
College of Nursing
References
1. World Health Organization. World health report 2006: Working together for health. Geneva: World Health Organization;
2006. Available at www.who.int/whr/2006/en.
2. World Health Organization. A universal truth: No health
without a workforce. Geneva: World Health Organization;
2013. Available at www.who.int/workforcealliance/knowledge/resources/GHWA_AUniversalTruthReport.pdf.
3. Horrocks S, Anderson E, Salisbury C. Systematic review of
whether nurse practitioners working in primary care can provide equivalent care to doctors. BMJ 2002;3:819–23
4. Naylor MD, Kurtzman ET. The role of nurse practitioners in
reinventing primary care. Health Affairs 2010;29:893–9.
5. Carter A, JE, Chochinov AH. Systematic review of the impact
of nurse practitioners on cost, quality of care, satisfaction and
wait times in the emergency department. CJEM 2007;9:
286–95.
Co-Infection with HIV Increases Risk for Decompensation in
Patients with HCV
Lo Re V, Kallan MJ, Tate JP, et al. Hepatic decompensation in antiretroviral-treated patients co-infected with HIV
and hepatitis C virus compared with hepatitis C virus-monoinfected patients. Ann Intern Med 2014;160:369–79.
Study Overview
Objective. To compare the incidence of hepatic decompensation in patients who are co-infected with HIV and
hepatitis C (HCV) and who underwent antiretroviral
treatment and patients who are HCV-monoinfected.
Design. Retrospective cohort study.
Participants and setting. This study used the Veterans Aging
Cohort Study Virtual Cohort (VACS-VC), which includes
electronic medical record data from patients who are HIVinfected and are receiving care at Veterans Affairs (VA)
medical facilities in the United States. Inclusion criteria for
patients who were co-infected were: detectable HCV RNA,
recently initiated antiretroviral therapy (ART), defined as
use of ≥ 3 antiretroviral drugs from 2 classes or ≥ 3 nucleowww.jcomjournal.com
side analogues within the VA system, HIV RNA level > 500
copies/mL within 180 days before starting ART, and were
seen in the VACS-VC for at least 12 months after initiating
ART. Inclusion criteria for patients who were monoinfected
with HCV were detectable HCV RNA, no HIV diagnosis
or antiretroviral prescriptions, and seen in the VACS-VC for
at least 12 months prior to inclusion into the study. Exclusion
criteria were hepatic decompensation, hepatocellular carcinoma, and liver transplant during the 12-month baseline
period or receipt of interferon-based HCV therapy.
Main outcome measure. The primary outcome was incident hepatic decompensation, defined as diagnosis of
ascites, spontaneous bacterial peritonitis, or esophageal
variceal hemorrhage at hospital discharge or 2 such outpatient diagnoses.
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Main results. A total of 10,359 patients met inclusion criteria and were enrolled between 1997 and 2010. Of these,
4280 were patients co-infected with HIV and HCV and
treated with antiretroviral agents and 6079 were patients
who were HCV-monoinfected. Age, race/ethnicity,
and history of diabetes, alcohol dependence or abuse, and
injection or non-injection drug were similar between the
2 groups. The majority of participants were men. HCV
genotype 1 was most prevalent in both groups. There
were more patients who had HCV RNA levels ≥ 400,000
IU/mL and/or ≥ 1x106 copies/mL in the co-infected
group versus the monoinfected group.
Hepatic decompensation occurred more frequently
among those who were co-infected and receiving ART
(271 [6.3%]) than among those who were monoinfected
(305 [5.0%], P = 0.004). The incidence rate was 9.5
events per 1000 person-years (95% CI, 7.6–11.9) among
patients co-infected with HIV and HCV and treated
with ART and 5.7 events per 1000 person-years (95%
CI, 4.4–7.4) among patients who were monoinfected.
Variceal hemorrhage was less common among patients
who were co-infected as compared to those who were
monoinfected (71 [26.2%] vs. 168 [55.1%], P < 0.001).
The proportion of patients with ascites (226 [83.4%] in
the co-infected group vs. 236 [77.4%] in the monoinfected, P = 0.070) and spontaneous bacterial peritonitis
(48 [17.7%] in the co-infected group vs. 68 [22.3%] in
the monoinfected, P = 0.171) were similar. After adjustment for age, race/ethnicity, diabetes, BMI, history of
alcohol abuse, injection or non-injection drug use, and
VA center patient volume, patients who were co-infected
and receiving ART had a higher rate of hepatic decompensation than monoinfected patients (hazard ratio, 1.83
[95% CI, 1.54–2.18]).
In subgroup analysis, rates of decompensation remained
higher even among co-infected patients who maintained
HIV RNA levels < 1000 copies/mL (hazard ratio 1.65
[95% CI 1.20–2.27])
Conclusion. Patients who were co-infected with HIV and
HCV and treated with ART had higher rates of hepatic
decompensation compared with patients monoinfected
with HCV. Good control of HIV viral loads in co-infected
patients may not be sufficient to improve health outcomes.
Commentary
Currently, it is estimated that there are 3.5 to 5.5 million
people in the United States infected with HCV, account400 JCOM September 2014 Vol. 21, No. 9
ing for about 1.5% of the population. Approximately 20%
to 40% of those infected will develop chronic infection
and 10% to 25% of these patients will progress to experience severe liver disease [1]. Yet of the 3.5 million people
who are thought be chronically infected with HCV, only
50% are diagnosed and are aware of the infection and a
mere 16% are treated for HCV [2].
Estimates suggest that about 10% of those with HCV
are also infected with HIV. In the era prior to ART for
HIV infections, patients with HIV and HCV most commonly died of HIV-related causes. In the post-ART era,
patients are surviving longer and are now experiencing
HCV-related comorbidities [3].
This study compares the incidence of hepatic decompensation in patients with HIV and HCV co-infection
who are undergoing treatment with ART and those with
HCV monoinfection. The results show that patients
who were co-infected and treated with ART had higher
incidence of hepatic decompensation as compared with
those who were monoinfected. This study’s strengths
are the large enrollment numbers (> 10,000 patients)
and the long follow-up periods (6.8 and 9.9 years for
the co-infected and monoinfected cohorts, respectively).
As the authors indicate, the weakness of this study is the
exclusion of the diagnosis of hepatic encephalopathy and
jaundice from their definition of hepatic decompensation. Their reasoning for doing so is that these frequently
occur due to unrelated causes, such as narcotic overdose
and biliary obstruction. It is possible that this resulted in
an underestimation of hepatic decompensation. Finally,
98.8% of the enrolled patients were male. The study
results cannot be generalized to women.
Since 2011, the availability of direct-acting antivirals
for the treatment of HCV has rapidly increased. These
new agents have improved treatment outcomes with
better sustained virological response, shorter treatment
duration, and better adverse event rates [4]. Telaprevir
and boceprevir were first-generation protease inhibitors,
and these were followed by simeprevir in 2013. Sofosbuvir also became available in 2013 as the first polymerase
inhibitor. These agents were and continue to be evaluated for use in HIV/HCV co-infected patients both in
treatment-naive and previously treated patients with
good outcomes. A fifth agent, faldaprevir, another protease inhibitor, is expected to become available this year
and others are in clinical trials [5]. Sustained virologic
response rates of 67% to 88% depending on genotype
with regimens using sofosbuvir in co-infected patients for
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OUTCOMES RESEARCH IN REVIEW
example, have been achieved, which are similar to rates in
monoinfected patients [6].
Applications for Clinical Practice
The authors found that management of HIV viral loads
to less than 1000 copies/mL reduced the risk for hepatic
decompensation. However, the difference in incidence
rates between those whose HIV load was < 1000 copies/mL and those whose viral load was ≥ 1000 copies/
mL was small (9.4 [95% CI, 5.4–16.2] vs. 9.6 [95% CI,
7.5–12.2]). The findings suggest that control of HIV
viral loads in co-infected patients is not sufficient to reduce the rate of liver complications. The authors propose
that earlier consideration be given to treatment of HCV
infection in co-infected patients to improve health outcomes. The American Association for the Study of Liver
Diseases and the Infectious Diseases Society of America
have published guidelines for the diagnosis and management of HCV [7]. The difference in hepatic decompensation rates between mono- and co-infected patients should
become less relevant as use of direct-acting antivirals
expands.
—Mayu O. Frank, MS, ANP-BC and Allison Squires, PhD, RN,
New York University College of Nursing
References
1. Action plan for the prevention, care, and treatment of viral hepatitis
(2014-2016). US Department of Health and Human Services; 2014.
Available at http://aids.gov/news-and-events/hepatitis/.
2. Yehia BR, Schranz AJ, Umscheid CA, Lo Re V. The treatment
cascade for chronic hepatitis C virus infection in the United States:
a systematic review and meta-analysis. PLOS One 2014;9:1–7.
3. Highleyman L. HIV/HCV coinfection: a new era of treatment.
BETA 2001; Fall/Winter: 30–47.
4. Shiffman ML. Hepatitis C virus therapy in the direct acting
antiviral era. Curr Opin Gastroenterol 2014;30:217–22.
5. Bichoupan K, Dieterich DT, Martel-Laferriere V. HIV-Hepatitis C virus co-infection in the era of direct-acting antivirals. Curr
HIV/AIDS Rep. 2014 July 5. [Epub ahead of print]
6. Sulkowski M, Rodriguez-Torres M, Lalezari J, et al. All-oral
therapy with sofosbuvir plus ribavirin for the treatment of HCV
genotype 1,2, and 3 infection in patients co-infected with HIV
(PHOTON-1). 64th annual meeting of the American Association for the Study of Liver Diseases. Washington, DC; Nov 2013.
7. The American Association for the Study of Liver Diseases and
the Infectious Diseases Society of America. Recommendations
for testing, managing, and treating hepatitis C. Accessed 1 Aug
2014 at www.hcvguidelines.org.
Copyright 2014 by Turner White Communications Inc., Wayne, PA. All rights reserved.
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Vol. 21, No. 9 September 2014 JCOM 401