0
Get Alert
Please Wait... Processing your request... Please Wait.
You must sign in to sign-up for alerts.

Please confirm that your email address is correct, so you can successfully receive this alert.

1
Article   |    
Relationship of Pharmaceutical Promotion to Antidepressant Switching and Adherence: A Retrospective Cohort Study
Richard A. Hansen, Ph.D.; Shih-Yin Chen, Ph.D.; Bradley N. Gaynes, M.D., M.P.H.; Matthew L. Maciejewski, Ph.D.
Psychiatric Services 2010; doi: 10.1176/appi.ps.61.12.1232
View Author and Article Information

Dr. Hansen was affiliated with the Division of Pharmaceutical Outcomes and Policy at the time of the study and Dr. Gaynes is with the Department of Psychiatry, both at the University of North Carolina, Chapel Hill. Dr. Hansen is now with the Department of Pharmacy Care Systems, Harrison School of Pharmacy, Auburn University, 207 Dunstan Hall, Auburn, AL 26849-5506 (e-mail: rah0019@auburn.edu). Dr. Chen is with the Center for Health Economics and Science Policy, United BioSource Corp., Lexington, Massachusetts. Dr. Maciejewski is with the Center for Health Services Research in Primary Care, U.S. Department of Veterans Affairs Medical Center, and the Division of General Internal Medicine, Department of Medicine, Duke University Medical Center, Durham, North Carolina. A portion of this work was presented at the annual meeting of the International Society for Pharmacoeconomics and Outcomes Research, May 16—20, 2009, Orlando, Florida.

Abstract

Objective: Patient nonadherence and early discontinuation of antidepressant treatment are common. Pharmaceutical promotion to consumers and physicians may influence this behavior. The objectives of this study were to explore whether promotional spending is related to early antidepressant switching, acute-phase adherence, and continuation-phase adherence. Methods: A retrospective cohort study was conducted with national promotional expenditure data merged with medical and prescription claims data from a large national health plan affiliated with i3 Innovus. Included were records for continuously insured adults with major depression who received a new prescription for an antidepressant: 5,010 were in the cohort assessed for switching, 4,457 were in the cohort assessed for acute-phase adherence, and 1,772 were in the cohort assessed for continuation-phase adherence. National promotional efforts were estimated by examining inflation-adjusted spending on direct-to-consumer advertising (DTCA) and physician detailing. Clinical guidelines were used to create proxies for aspects of treatment outcomes, including antidepressant switching and adherence in the acute phase and adherence in the continuation phase. Logistic regression models estimated the association between promotional variables and these outcomes. Results: Patients taking medications that were more highly promoted to physicians were less likely to switch medications (odds ratio [OR]=.61) and were more likely to be adherent during the acute phase of treatment (OR=1.13). DTCA had little effect on switching or antidepressant adherence. Conclusions: Detailing to physicians was associated with lower rates of medication switching and had a positive relationship with patient adherence during early antidepressant treatment. This finding indicates that certain aspects of promotion may have beneficial effects on antidepressant use. (Psychiatric Services 61:1232—1238, 2010)

Abstract Teaser
Figures in this Article

Spending on pharmaceutical promotion to patients increased 330% between 1996 and 2005, from $985 million to $4.2 billion, while promotion to physicians increased 81%, from $3.7 billion to $6.7 billion (1). Promotional spending overall accounts for roughly 18% of U.S. pharmaceutical sales (1). Promotion to physicians ("detailing") has been shown to affect prescribing practices (2), and direct-to-consumer advertising (DTCA) has been associated with inappropriate medication use and increased drug expenditures (3,4,5). Further, promotional spending has been associated with increased diagnosis and treatment of patients who had not previously received a diagnosis (6,7,8).

Prior studies have found that patient-provider discussions about DTCA increase the likelihood of new depression diagnoses, as well as the likelihood of receiving an antidepressant once a patient is given a diagnosis (8,9,10). Drug promotion may also improve adherence, thus increasing the likelihood that a patient receives guideline-concordant treatment (7,11,12,13). Promotion-related improvements in adherence might be especially important because evidence suggests that roughly 40% of patients discontinue antidepressants during the first 30 days of treatment and 75% discontinue after 90 days (14). Discontinuing or switching medications too early may preclude therapeutic benefit.

Even though antidepressants have been heavily promoted, only one study has examined whether antidepressant promotion influences whether patients use antidepressant medications for an appropriate duration (9). Among 10,409 individuals with 11,306 unique depressive episodes between 1997 and 2000, DTCA of competing products was positively associated with the likelihood that an individual completed an appropriate duration of treatment (odds ratio [OR]=1.3, 95% confidence interval [CI]=1.06—1.62 for the highest quartile of spending), but detailing to physicians had no impact. It is noteworthy that the study represented the early years of DTCA, reflecting a time immediately after changes in the rules on prescription drug advertising. Further examination of the relationship between promotion and antidepressant use is warranted because promotional spending increased significantly after this time, the antidepressant market has evolved (with new drugs, new formulations, and increased availability of generics) (15), and limited evidence of the benefits and harms of promotion exists. Previous work also has not considered specific aspects of antidepressant use that might be affected by promotion.

The purpose of this study was to explore how physician detailing and DTCA affected guideline-concordant antidepressant use (specifically, early switching and medication adherence) among patients newly diagnosed as having major depression.

+

Data sources

Medical and prescription claims from a large national health plan affiliated with i3 Innovus were obtained for the years 2000—2004. National promotional data were obtained from IMS Health for a comparable period. The IMS Health Integrated Promotional Services data are used to estimate dollars spent in the United States on provider detailing, patient samples, journal advertising, and DTCA by month for each product. The antidepressant spending data represent the relative intensity of promotional efforts for each product over time. Product-level promotional data were linked to person-level claims data by date on the basis of the drug received at cohort entry. The study was approved by the University of North Carolina Institutional Review Board.

+

Study sample

On the basis of diagnoses from inpatient and outpatient medical claims, we identified 18,759 patients who had new diagnoses of single-episode major depressive disorder (ICD-9 codes 296.20—296.24) between June 1, 2000, and December 31, 2002, and were continuously eligible for both medical and pharmacy benefits for six months before and at least two years after the index diagnosis. [A chart showing sample and cohort selection during the study period is available in an online supplement to this article at ps.psychiatryonline.org.] To be "newly diagnosed," a patient could have no depression diagnosis within the previous six months.

Patients were excluded from consideration for the study if they were younger than 18 years (N=1,474), did not fill a prescription for a second-generation antidepressant within 45 days after their index diagnosis (N=10,252), or had an antidepressant claim within six months before the index diagnosis (N=1,226). An additional 533 individuals were excluded because they had an ICD-9 diagnosis code for schizophrenia or bipolar disorder (including codes 290.xx—295.xx, 296.25, 296.26, 296.3x, 297.xx—316.xx) during the study period. Patients prescribed trazodone, fluvoxamine, and a specific formulation of fluoxetine (Sarafem) were excluded because of a small, drug-specific sample (N=18). Finally, patients were excluded if they had evidence of more than 30 days of duplication in antidepressant treatment ("augmenters") or switched medications more than one time over the course of follow-up (N=246). These exclusions provided a final sample of 5,010 patients with a diagnosis of major depression who filled a prescription for a second-generation antidepressant (bupropion, citalopram, escitalopram, fluoxetine, mirtazapine, nefazodone, paroxetine, sertraline, or venlafaxine) within 45 days of the index diagnosis.

We created three unique cohorts of patients to examine switching and adherence. The first cohort (N=5,010) was used to assess the impact of DTCA and physician detailing on acute-phase medication switching. The second cohort (N=4,457) was used to assess the impact of DTCA and detailing on acute-phase adherence and excluded all patients who switched medications during the acute phase (N=553). The third cohort (N=1,772) was used to assess the impact of DTCA and detailing on continuation-phase adherence and excluded all patients in the second cohort who did not complete the acute phase of treatment (N=2,685).

+

Outcome variables

Switching. Patients were defined as medication switchers if they initiated a second antidepressant during the first 90 days after the index antidepressant prescription without evidence of overlapping use of medications in a 30-day supply of both antidepressant medications (in other words, "nonaugmenters"). Although we cannot determine why a switch occurred, switching in the acute phase of treatment should not be influenced by promotion. More specifically, clinically appropriate changes from one antidepressant to another during the acute phase of treatment may be influenced by the drugs' efficacy, adverse events, or costs—but not by promotional spending. We focused analyses on promotional spending by examining the drug initially prescribed, rather than the subsequent drug (or drugs) received.

Adherence. Adherence was defined as a modified medication possession ratio (MPR) for the acute and continuation phases of treatment (16,17). The MPR reflects the degree to which the patient had medication available during the treatment interval. MPR in the acute phase was calculated as the total days of medication supplied over the first 90 days (corrected for any additional medication on hand at the end of the 90-day interval) divided by the total days in the acute phase (90 days). The continuation-phase adherence variable was defined similarly, with an MPR for days 91—270, which conservatively represents the expected continuation phase of treatment, according to practice guidelines (18,19,20). The continuation-phase MPR was adjusted for expected medication supply carried over from acute-phase treatment and was censored for oversupply beyond 270 days. For both the acute and continuation phases, patients were considered nonadherent if they had an MPR <80% or had a single gap in medication supply that exceeded 1.5 times the days' supply of the previous fill (that is, extending 45 days beyond a 30-day supply) (21,22).

+

Promotion-related explanatory variables

Monthly data for spending on samples, detailing, journal advertising, and DTCA were obtained from IMS Health for bupropion, citalopram, escitalopram, fluoxetine, mirtazapine, nefazodone, paroxetine, sertraline, and venlafaxine. These data do not represent the effectiveness of promotion but provide an ecological estimate of its relative intensity (23). We considered each type of spending, but ultimately included only the detailing and DTCA variables in our model. This decision avoided problems with multicollinearity because the promotional expenditures targeted to prescribers were highly correlated.

Promotional expenditures for DTCA and detailing were adjusted to 2004 dollars using a medical component of the consumer price index (24). We then constructed cumulative spending in each person-month for DTCA and detailing by summing current-month spending with discounted spending for the previous six months, based on a discount rate of 11% per month for DTCA and .3% per month for spending on detailing (9,25). DTCA and detailing spending values were then assigned to patients on the basis of the drug they received and the date at which they entered the cohort. These promotional spending values were created separately for the acute and continuation phases by averaging the cumulative spending in each month over the duration of each treatment phase.

These average cumulative spending variables for DTCA and detailing were used as the explanatory variables of interest in the switching and adherence regressions. We specified them both continuously and categorically in each model. The continuous form of spending was modeled as total DTCA spending for the antidepressant that a patient initially received ("own product DTCA"), total DTCA spending for all other antidepressants that the patient did not receive ("other product DTCA"), total detail spending to physicians for the antidepressant that a patient initially received ("own product detailing"), and total detail spending to physicians for all other antidepressants that the patient did not receive ("other product detailing"). The categorical form of spending was modeled as quartiles of own product DTCA, quartiles of other product DTCA, quartiles of own product detailing, and quartiles of other product detailing. Quartiles were used for comparison with previous analyses (9).

We also examined overall DTCA and detailing spending without separating own product and other product, but the results were not significant and are not presented here.

+

Analysis

Descriptive statistics of the explanatory variables for each cohort were calculated. Logistic regressions were used to estimate the association between promotional variables and each of three outcomes: antidepressant switching, adherence in the acute phase, and adherence in the continuation phase. Models were then rerun with substitution of the four continuous spending variables on own product DTCA, other product DTCA, own product detailing, and other product detailing with categorical quartiles of these variables. All models controlled for the following: patient age, gender, patient out-of-pocket cost for the index antidepressant, the Deyo version of the Charlson Comorbidity Index calculated on the basis of the six-month period before the index diagnosis (26,27), the specific antidepressant initially received, specialty of the prescriber, and region. We also controlled for time trends using indicators for quarter rather than month (as in a previous study) (9) because the correlation between month and detailing spending was high (.44—.66). Multicollinearity of this size would preclude identification of the unique contribution of DTCA and detailing if month were included in the models. All analyses were conducted with SAS, version 9.1.

Significant variability in DTCA was observed by drug and over time, whereas less variability in detailing spending was observed by drug and over time (Figure 1). Monthly DTCA spending was highest for bupropion, paroxetine, and sertraline, with average total unadjusted market spending exceeding $17 million per month for the antidepressant class over the course of the study. Detailing expenditures were highest for escitalopram, citalopram, and sertraline, with average total unadjusted market spending exceeding $38 million per month for the antidepressant class over the course of the study. [Figures showing drug-specific DTCA spending and detailing spending are available in an online supplement to this article at ps.psychiatryonline.org.]

Table 1 summarizes the demographic, treatment, copayment, and comorbidity characteristics of the sample.

+

Relationship of promotion with switching

Eleven percent (N=533) of patients switched from one antidepressant to another at some point during the 90 days of the acute phase of treatment. When adjusted for covariates, spending on own product detailing had a protective relationship with switching (OR=.61) (Table 2, model 1), which indicates that patients initially prescribed an antidepressant in tandem with high detailing spending were less likely to switch to an alternative antidepressant. This finding was consistent in model 2 (OR=.48—.49, all comparisons significant at p<.05), which replaced continuous promotional spending variables with categorical variables. Other product detailing, own product DTCA, and other product DTCA were not associated with medication switching in either of the models.

+

Relationship of promotion with acute-phase adherence

Of the 4,457 patients who did not switch medications during the acute phase, 1,772 (40%) were adherent to their antidepressants during this phase of treatment. In logistic regressions that adjusted for covariates, spending on own product detailing (Table 2, model 1) was positively and significantly associated with better acute-phase adherence (OR=1.13). This association was significant (≥$48.3 million: OR=1.51) for only the products in the highest quartile of detailing spending (Table 2, model 2). Spending on DTCA and other product detailing was not statistically significantly associated with acute-phase adherence in either model.

+

Relationship of promotion with continuation-phase adherence

Among the 1,772 patients who were adherent during the acute phase of treatment, 786 (44%) patients completed the continuation phase by being adherent for another six months. When modeled as continuous variables, own product and other product DTCA and detailing spending were not significantly associated with adherence in the continuation phase (Table 2, model 1). However, other product DTCA was positively and significantly associated with adherence in the continuation phase ($60 million to $75 million, OR=1.62; $76 million to $91 million, OR=1.66) when assessed with its categorical spending variables (Table 2, model 2). In other words, the likelihood that patients would be adherent through the continuation phase of treatment was higher when the magnitude of DTCA was high for other products in the market. Own product DTCA, own product detailing, and other product detailing were not associated with continuation-phase adherence when these types of promotion were assessed with categorical variables.

Antidepressants are commonly prescribed for depressive disorders and were heavily promoted during the time of this study. For example, in 2004, more than $237 million was spent on DTCA related to antidepressants in the United States, which represents 12% of the roughly $2 billion that was spent on antidepressant promotion to physicians via detailing, samples, and journal advertising. Although DTCA accounts for a small percentage of promotional spending in the pharmaceutical market, the positive and negative effects of DTCA have been hotly debated (28,29,30). DTCA has been portrayed negatively because of increased burden on physicians' time, inappropriate prescribing, and increased prescription drug costs (11,31,32). However, DTCA also may educate consumers, increase patient treatment seeking, and motivate patients to be adherent.

Our study showed that patients with major depression who initially received antidepressants that were promoted with high detailing spending were less likely to switch medications in the acute phase, which suggests that heavy promotion to prescribers was related to some degree of resistance to early drug switching. This finding could be a sign of "selling" by prescribers, or, because detailing is most prevalent early in a product's lifecycle, this could just be a reflection of preferences for the newest thing. Switching from one antidepressant to another may be appropriate if the switch is driven by side effects, lack of effectiveness, or cost-related nonadherence. If high detailing spending kept patients from switching to medications that they were better able to tolerate or better able to afford, then patients' interests were not well served. On the other hand, patients for whom an unnecessary switch was avoided in response to high detailing spending may have been more adherent, avoided unnecessary alternative treatments, and achieved therapeutic benefit sooner than other patients (33,34).

We also found that patients who initially received products associated with high detailing spending were more likely to be adherent in the acute phase of treatment. On the other hand, no statistically significant relationship was observed between DTCA and adherence in the acute phase. Because our measure of adherence reflected patients' medication-usage behavior, it is interesting that physician-directed promotion but not patient-directed promotion was related to patient adherence. One possible explanation is that detailing leads to greater prescriber awareness of antidepressant use and perhaps more enthusiastic encouragement for patients to remain on that antidepressant throughout the acute phase. This finding might also indicate that DTCA is not very effective for changing adherence behavior.

Among the cohort of patients that successfully completed the acute phase of treatment, we observed a higher likelihood of adherence in the continuation phase when there was high DTCA spending for alternative antidepressants in the market. Although this finding is counterintuitive, it is consistent with a small positive association between other product DTCA spending and appropriate duration of antidepressant treatment found by Donohue and colleagues (9). The effect of individual product advertising may not be what matters most, but rather the overall effect of advertising for medications used to treat the same condition. However, this finding also might be related to changes in promotional strategy that occurred when this study was conducted, especially given the entry of generic products into the market and product reformulations (15). We might also have been observing the effect of unmeasured factors, such as formulary changes.

Our study is subject to several limitations. First, our measure of promotional intensity was ecological, and we can only infer that variability in promotional spending by drug and over time was related to our outcome. We were unable to capture person-level variation in promotional spending or differences in the content of the advertising campaigns. Second, we cannot distinguish clinically appropriate switching or appropriate nonadherence.

Third, our results may be sensitive to study design considerations. We defined the acute phase as 90 days to reflect an average duration of this phase of treatment and the days of supply commonly dispensed via prescription (30-day increments). We chose to limit continuation-phase follow-up to days 91—270 of treatment to capture an average recommended duration of ongoing treatment after response to medication in the acute phase (18,19,20).

Fourth, the generalizability of this privately insured sample is limited, and there may be important differences in this population (such as in income and education) compared with other groups, such as those with Medicaid or Medicare or those who are uninsured. Fifth, we did not have data on some potentially important variables (education, for example), and simply controlling for demographic variables such as age and sex may not adequately delineate the relationship between promotion, switching, and adherence. Finally, we assessed adherence via prescription claims rather than actual medication consumption. Although claims may not reflect actual behavior, refill adherence has been found to be sensitive to clinical outcomes and is widely used to assess adherence (17,35).

Our findings suggest that detailing has an impact on switching and adherence during the acute phase of antidepressant treatment, a time when patients with depression are most vulnerable to nonadherence. DTCA for the initial product prescribed did not significantly influence acute-phase switching or adherence, but DTCA for alternative antidepressants had an impact on longer-term adherence. These findings indicate that certain aspects of promotion increase the likelihood that patients receive guideline-concordant antidepressant treatment.

A portion of this work was funded by the new investigator program of the American Association of Colleges of Pharmacy. Dr. Hansen was supported by grant K12RR023248 from the National Institutes of Health at the time of this work. The authors thank Emily Brouwer, Pharm.D., for her contributions to data management; David Ridley, Ph.D., for his contribution to study design; and Julie Donohue, Ph.D., for her insightful comments on the manuscript.

Dr. Hansen has received consulting fees and research support from Takeda Pharmaceuticals and GlaxoSmithKline. Dr. Gaynes has received consulting fees and research support from Bristol-Myers Squibb, M-3 Information, and Novartis, and he has served as an advisor to Bristol-Myers Squibb. Dr. Maciejewski has received consulting fees from Takeda Pharmaceuticals. Dr. Chen reports no competing interests.

Donohue JM, Cevasco M, Rosenthal MB: A decade of direct-to-consumer advertising of prescription drugs. New England Journal of Medicine 357:673—681, 2007
 
Berndt ER, Bui L, Reiley DR, et al: Information, marketing, and pricing in the US antiulcer drug market. American Economic Review 85:100—105, 1995
 
Wolfe SM: Direct-to-consumer advertising: education or emotion promotion? New England Journal of Medicine 346:524—526, 2002
 
Hollon MF: Direct-to-consumer marketing of prescription drugs: creating consumer demand. JAMA 281:382—384, 1999
 
Spence MM, Teleki SS, Cheetham TC, et al: Direct-to-consumer advertising of COX-2 inhibitors: effect on appropriateness of prescribing. Medical Care Research and Review 62:544—559, 2005
 
Holmer AF: Direct-to-consumer prescription drug advertising builds bridges between patients and physicians. JAMA 281:380—382, 1999
 
Holmer AF: Direct-to-consumer advertising: strengthening our health care system. New England Journal of Medicine 346:526—528, 2002
 
Feldman MD, Franks P, Epstein RM, et al: Do patient requests for antidepressants enhance or hinder physicians' evaluation of depression? A randomized controlled trial. Medical Care 44:1107—1113, 2006
 
Donohue JM, Berndt ER, Rosenthal M, et al: Effects of pharmaceutical promotion on adherence to the treatment guidelines for depression. Medical Care 42:1176—1185, 2004
 
Kravitz RL, Epstein RM, Feldman MD, et al: Influence of patients' requests for direct-to-consumer advertised antidepressants: a randomized controlled trial. JAMA 293:1995—2002, 2005
 
Almasi EA, Stafford RS, Kravitz RL, et al: What are the public health effects of direct-to-consumer drug advertising? PLoS Medicine 3:e145, 2006
 
Wosinska M: Direct-to-consumer advertising and drug therapy compliance. Journal of Marketing Research 42:323—332, 2005
 
Bradford WD, Kleit AN, Nietert PJ, et al: How direct-to-consumer television advertising for osteoarthritis drugs affects physicians' prescribing behavior. Health Affairs (Millwood) 25:1371—1377, 2006
 
Olfson M, Marcus SC, Tedeschi M, et al: Continuity of antidepressant treatment for adults with depression in the United States. American Journal of Psychiatry 163:101—108, 2006
 
Huskamp HA, Donohue JM, Koss C, et al: Generic entry, reformulations and promotion of SSRIs in the US. Pharmacoeconomics 26:603—616, 2008
 
Steiner JF, Koepsell TD, Fihn SD, et al: A general-method of compliance assessment using centralized pharmacy records: description and validation. Medical Care 26:814—823, 1988
 
Steiner JF, Prochazka AV: The assessment of refill compliance using pharmacy records: methods, validity, and applications. Journal of Clinical Epidemiology 50:105—116, 1997
 
Depression Guideline Panel: Clinical Practice Guideline No 5: Depression in Primary Care: Volume 2. Treatment of Major Depression. Rockville, Md, US Department of Health and Human Services, Agency for Health Care Policy and Research, 1993
 
American Psychiatric Association: Practice guideline for the treatment of patients with major depressive disorder (revision). American Journal of Psychiatry 157(Apr suppl):1—45, 2000
 
Qaseem A, Snow V, Denberg TD, et al: Using second-generation antidepressants to treat depressive disorders: a clinical practice guideline from the American College of Physicians. Annals of Internal Medicine 149:725—733, 2008
 
Katon W, Cantrell CR, Sokol MC, et al: Impact of antidepressant drug adherence on comorbid medication use and resource utilization. Archives of Internal Medicine 165:2497—2503, 2005
 
Cantrell CR, Eaddy MT, Shah MB, et al: Methods for evaluating patient adherence to antidepressant therapy: a real-world comparison of adherence and economic outcomes. Medical Care 44:300—303, 2006
 
Hansen RA, Droege M: Methodological challenges surrounding direct-to-consumer advertising research: the measurement conundrum. Research in Social and Administrative Pharmacy 1:331—347, 2005
 
US Department of Labor: Consumer Price Index Summary. Available at www.bls.gov/cpi. Accessed July 30, 2007
 
Ling DC, Berndt ER, Kyle MK: Deregulating direct-to-consumer marketing of prescription drugs: effects on prescription and over-the-counter product sales. Journal of Law and Economics 45:691—723, 2002
 
Charlson ME, Pompei P, Ales KL, et al: A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases 40:373—383, 1987
 
Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal of Clinical Epidemiology 45:613—619, 1992
 
Saul S: Senate leader calls for limits on drug ads. New York Times, July 2, 2005
 
Committee on the Assessment of the US Drug Safety System, Baciu A, Stratton K, et al: The Future of Drug Safety: Promoting and Protecting the Health of the Public. Washington, DC, National Academies Press, 2006
 
Shuchman M: Drug risks and free speech: can Congress ban consumer drug ads? New England Journal of Medicine 356:2236—2239, 2007
 
Wilkes MS, Bell RA, Kravitz RL: Direct-to-consumer prescription drug advertising: trends, impact, and implications. Health Affairs (Millwood) 19(2):110—128, 2000
 
Bell RA, Kravitz RL, Wilkes MS: Direct-to-consumer prescription drug advertising and the public. Journal of General Internal Medicine 14:651—657, 1999
 
Mullins CD, Shaya FT, Meng F, et al: Persistence, switching, and discontinuation rates among patients receiving sertraline, paroxetine, and citalopram. Pharmacotherapy 25:660—667, 2005
 
Mischoulon D, Nierenberg AA, Kizilbash L, et al: Strategies for managing depression refractory to selective serotonin reuptake inhibitor treatment: a survey of clinicians. Canadian Journal of Psychiatry 45:476—481, 2000
 
Bryson CL, Au DH, Young B, et al: A refill adherence algorithm for multiple short intervals to estimate refill compliance (ReComp). Medical Care 45:497—504, 2007
 
 
Promotional spending trends for second-generation antidepressants, 2000—2004
Table 1  Baseline characteristics of three cohorts of patients assessed for antidepressant switching and adherence, by treatment phase
Table 2  Relationship of promotion to acute-phase switching, acute-phase adherence, and continuation-phase adherence

Figure 1  Promotional spending trends for second-generation antidepressants, 2000—2004
Table 1  Baseline characteristics of three cohorts of patients assessed for antidepressant switching and adherence, by treatment phase
Table 2  Relationship of promotion to acute-phase switching, acute-phase adherence, and continuation-phase adherence
+

References

Donohue JM, Cevasco M, Rosenthal MB: A decade of direct-to-consumer advertising of prescription drugs. New England Journal of Medicine 357:673—681, 2007
 
Berndt ER, Bui L, Reiley DR, et al: Information, marketing, and pricing in the US antiulcer drug market. American Economic Review 85:100—105, 1995
 
Wolfe SM: Direct-to-consumer advertising: education or emotion promotion? New England Journal of Medicine 346:524—526, 2002
 
Hollon MF: Direct-to-consumer marketing of prescription drugs: creating consumer demand. JAMA 281:382—384, 1999
 
Spence MM, Teleki SS, Cheetham TC, et al: Direct-to-consumer advertising of COX-2 inhibitors: effect on appropriateness of prescribing. Medical Care Research and Review 62:544—559, 2005
 
Holmer AF: Direct-to-consumer prescription drug advertising builds bridges between patients and physicians. JAMA 281:380—382, 1999
 
Holmer AF: Direct-to-consumer advertising: strengthening our health care system. New England Journal of Medicine 346:526—528, 2002
 
Feldman MD, Franks P, Epstein RM, et al: Do patient requests for antidepressants enhance or hinder physicians' evaluation of depression? A randomized controlled trial. Medical Care 44:1107—1113, 2006
 
Donohue JM, Berndt ER, Rosenthal M, et al: Effects of pharmaceutical promotion on adherence to the treatment guidelines for depression. Medical Care 42:1176—1185, 2004
 
Kravitz RL, Epstein RM, Feldman MD, et al: Influence of patients' requests for direct-to-consumer advertised antidepressants: a randomized controlled trial. JAMA 293:1995—2002, 2005
 
Almasi EA, Stafford RS, Kravitz RL, et al: What are the public health effects of direct-to-consumer drug advertising? PLoS Medicine 3:e145, 2006
 
Wosinska M: Direct-to-consumer advertising and drug therapy compliance. Journal of Marketing Research 42:323—332, 2005
 
Bradford WD, Kleit AN, Nietert PJ, et al: How direct-to-consumer television advertising for osteoarthritis drugs affects physicians' prescribing behavior. Health Affairs (Millwood) 25:1371—1377, 2006
 
Olfson M, Marcus SC, Tedeschi M, et al: Continuity of antidepressant treatment for adults with depression in the United States. American Journal of Psychiatry 163:101—108, 2006
 
Huskamp HA, Donohue JM, Koss C, et al: Generic entry, reformulations and promotion of SSRIs in the US. Pharmacoeconomics 26:603—616, 2008
 
Steiner JF, Koepsell TD, Fihn SD, et al: A general-method of compliance assessment using centralized pharmacy records: description and validation. Medical Care 26:814—823, 1988
 
Steiner JF, Prochazka AV: The assessment of refill compliance using pharmacy records: methods, validity, and applications. Journal of Clinical Epidemiology 50:105—116, 1997
 
Depression Guideline Panel: Clinical Practice Guideline No 5: Depression in Primary Care: Volume 2. Treatment of Major Depression. Rockville, Md, US Department of Health and Human Services, Agency for Health Care Policy and Research, 1993
 
American Psychiatric Association: Practice guideline for the treatment of patients with major depressive disorder (revision). American Journal of Psychiatry 157(Apr suppl):1—45, 2000
 
Qaseem A, Snow V, Denberg TD, et al: Using second-generation antidepressants to treat depressive disorders: a clinical practice guideline from the American College of Physicians. Annals of Internal Medicine 149:725—733, 2008
 
Katon W, Cantrell CR, Sokol MC, et al: Impact of antidepressant drug adherence on comorbid medication use and resource utilization. Archives of Internal Medicine 165:2497—2503, 2005
 
Cantrell CR, Eaddy MT, Shah MB, et al: Methods for evaluating patient adherence to antidepressant therapy: a real-world comparison of adherence and economic outcomes. Medical Care 44:300—303, 2006
 
Hansen RA, Droege M: Methodological challenges surrounding direct-to-consumer advertising research: the measurement conundrum. Research in Social and Administrative Pharmacy 1:331—347, 2005
 
US Department of Labor: Consumer Price Index Summary. Available at www.bls.gov/cpi. Accessed July 30, 2007
 
Ling DC, Berndt ER, Kyle MK: Deregulating direct-to-consumer marketing of prescription drugs: effects on prescription and over-the-counter product sales. Journal of Law and Economics 45:691—723, 2002
 
Charlson ME, Pompei P, Ales KL, et al: A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases 40:373—383, 1987
 
Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal of Clinical Epidemiology 45:613—619, 1992
 
Saul S: Senate leader calls for limits on drug ads. New York Times, July 2, 2005
 
Committee on the Assessment of the US Drug Safety System, Baciu A, Stratton K, et al: The Future of Drug Safety: Promoting and Protecting the Health of the Public. Washington, DC, National Academies Press, 2006
 
Shuchman M: Drug risks and free speech: can Congress ban consumer drug ads? New England Journal of Medicine 356:2236—2239, 2007
 
Wilkes MS, Bell RA, Kravitz RL: Direct-to-consumer prescription drug advertising: trends, impact, and implications. Health Affairs (Millwood) 19(2):110—128, 2000
 
Bell RA, Kravitz RL, Wilkes MS: Direct-to-consumer prescription drug advertising and the public. Journal of General Internal Medicine 14:651—657, 1999
 
Mullins CD, Shaya FT, Meng F, et al: Persistence, switching, and discontinuation rates among patients receiving sertraline, paroxetine, and citalopram. Pharmacotherapy 25:660—667, 2005
 
Mischoulon D, Nierenberg AA, Kizilbash L, et al: Strategies for managing depression refractory to selective serotonin reuptake inhibitor treatment: a survey of clinicians. Canadian Journal of Psychiatry 45:476—481, 2000
 
Bryson CL, Au DH, Young B, et al: A refill adherence algorithm for multiple short intervals to estimate refill compliance (ReComp). Medical Care 45:497—504, 2007
 
+
+

CME Activity

There is currently no quiz available for this resource. Please click here to go to the CME page to find another.
Submit a Comments
Please read the other comments before you post yours. Contributors must reveal any conflict of interest.
Comments are moderated and will appear on the site at the discertion of APA editorial staff.

* = Required Field
(if multiple authors, separate names by comma)
Example: John Doe



Web of Science® Times Cited: 3

Related Content
Articles
Books
Manual of Clinical Psychopharmacology, 7th Edition > Chapter 2.  >
Textbook of Psychotherapeutic Treatments > Chapter 5.  >
Manual of Clinical Psychopharmacology, 7th Edition > Chapter 11.  >
Manual of Clinical Psychopharmacology, 7th Edition > Chapter 11.  >
The American Psychiatric Publishing Textbook of Psychopharmacology, 4th Edition > Chapter 19.  >
Topic Collections
Psychiatric News
APA Guidelines