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Screening for depression in high-risk groups: prospective cohort study in general practice

  • Kim D. Baas (a1), Karin A. Wittkampf (a2), Henk C. van Weert (a3), Peter Lucassen (a4), Jochanan Huyser (a1), Henk van den Hoogen (a5), Eloy van de Lisdonk (a5), Patrick E. Bindels (a3), Claudi L. Bockting (a3), Henricus G. Ruhé (a6) and Aart H. Schene (a6)...
Abstract
Background

Currently only about half of the people who have major depressive disorder are detected during regular health care. Screening in high-risk groups might be a possible solution.

Aims

To evaluate the effectiveness of selective screening for major depressive disorder in three high-risk groups in primary care: people with mental health problems, people with unexplained somatic complaints and people who frequently attend their general practitioner.

Method

Prospective cohort study among 2005 people in high-risk groups in three health centres in The Netherlands.

Results

Of the 2005 people identified, 1687 were invited for screening and of these 780 participated. Screening disclosed 71 people with major depressive disorder: 36 (50.7%) already received treatment, 14 (19.7%) refused treatment and 4 individuals did not show up for an appointment. As a final result of the screening, 17 individuals (1% of 1687) started treatment for major depressive disorder.

Conclusions

Screening for depression in high-risk populations does not seem to be effective, mainly because of the low rates of treatment initiation, even if treatment is freely and easily accessible.

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Corresponding author
Aart H. Schene, Department of Psychiatry, Academic Medical Center, (Room PA1-132), Meibergdreef 5 1105 AZ Amsterdam, The Netherlands. Email: a.h.schene@amc.uva.nl
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Declaration of interest

None.

Footnotes
References
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Screening for depression in high-risk groups: prospective cohort study in general practice

  • Kim D. Baas (a1), Karin A. Wittkampf (a2), Henk C. van Weert (a3), Peter Lucassen (a4), Jochanan Huyser (a1), Henk van den Hoogen (a5), Eloy van de Lisdonk (a5), Patrick E. Bindels (a3), Claudi L. Bockting (a3), Henricus G. Ruhé (a6) and Aart H. Schene (a6)...
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eLetters

Screening on depression in primary care high risk groups.

Aart H. Schene, MD, PhD
22 October 2009

Dr. Mitchell raises two interesting issues:

1) the way we calculated results of the screening procedure, in particular the number needed to screen to treat one additional patient

2) the PHQ-9 as a screening-instrument.

1.As dr. Mitchell mentions our study was indeed a screening implementation study. We wanted to learn if screening in high risk groups could detect a substantial number of so far not detected and treatable patients with depression. For this we conducted a pragmatic study and determined the gain of a stepped care screening (and treatment) program inreal practice, with real doctors and real patients. A general practitionerwho wants to screen his patients can read what to expect. Failures (refusals, no-shows, misclassifications) are inherent to such conditions and should be incorporated in the calculations.

We defined our target population and included patients (N=2005) from the GPs medical files and surgery. Our screening cascade showed 17 new patients that could be treated for depression. Perhaps this calculation isa bit optimistic because treatment was directly available without costs, which is not always the case.

Dr. Mitchell makes a comparison with a drug trial. Unfortunately we do not think this comparison makes the interpretation of our data more easy. We consider as our screen the PHQ and we use the SCID as the reference diagnostic standard. So the 780 patients who returned the PHQ and gave Informed Consent form the screened population. From there we count downstairs to the number of detected cases and upstairs to the number needed to be invited for the screening to be able to screen those 780 patients.

There can be discussion about the way we corrected for patients that did not comply with the program. We presented each step (with number of people who refused, did not attend and the reasons therefore), so that readers can make their own judgements, as dr. Mitchell has done. However we disagree with his interpretation. If we stay in his analogy with a drugtrial, then an intention to treat analysis is the best analysis. That means that non compliance should be incorporated in the number needed to treat (or screen). Starting the analysis with the number of patients that completed the SCID (as dr. Mitchell does) provides the GP with the number of patients he has to see, after a pre-screen with the PHQ-9.

2.It is correct that the PHQ-9 misses some cases, although not as many as dr. Mitchell supposes. We used the PHQ-9 in the screening mode (cut off score ¡Ý 10) and not in the diagnostic mode (algorithm). Sensitivity of the screening-mode is 0.93, not 0.77. (1) However, a GP whouses the PHQ-9 will follow the results of the screening and invite patients with a positive score for clinical evaluation, thus also missing patients with a score below threshold. We unfortunately do not have SCID data of those who scored negative on the PHQ.

Henk van Weert, MD, PhDAart Schene, MD, PhD

1. Wittkampf K, Ravesteijn H, Baas K, Hoogen H van de, Schene A, Bindels P, Lucassen P, Lisdonk E van de, Weert H van. The accuracy of the Patient Health Questionnaire-9 in detecting depression and measuring depression severity in high-risk groups in primary care. General Hospital Psychiatry 2009;31:451-459

Declaration of interest: none.
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Interpretation of Screening Implementation Studies

Alex J Mitchell, Consultant in Liaison Psychiatry
29 July 2009



Baas and colleagues report some very valuable findings based on a screening implementation study in Dutch general practice. In particular they document that converting detections into treatment success is difficult in clinical practice and that many individuals with depression are unable or unwilling to accept help. However, I must disagree with their interpretation that it is necessary to screen 118 (17 of 2005) “high risk” people to treat 1 new case. Let me illustrate this with an analogy of a drug trial for drug X. Lets a say I conduct a trial of drug X in primary care among 2005 individuals. Of 2005 approached, 780 consent to take X and of these 226 have an initial response. The main question I would be asked is how many of the 780 were actually depressed? I don’t have this figure but I can say that of the 226 responders, 173 were given a SCID interview and of these 71 are depressed. Further, of the 71, unknown to me 36 were already receiving treatment (even though the protocol asked GPs to exclude those people with depression already known to them) and ultimately only 17 accepted treatment. Can I conclude from my trial of X that it is not a successful drug because only 17 were newly treated? No. I have demonstrated the difficulty conducted a pragmatic trial in primary care but I don’t really know the success of X and I don’t have any comparative placebo (TAU) arm.

What does this mean for the interpretation of the paper from Baas and colleagues? From the authors data the most critical step for useful interpretation of screening yield is revealed from those who have 1. the screen and 2. the criterion reference (gold standard, ie SCID). Thus I suggest that

A. the number of detected cases per screen (who had a criterion diagnosis) = 71/173 (41%)B. The number of newly treated cases per screen (who had a criterion diagnosis) = 35/173 (20%)C. The number of helped cases per screen (who had a criterion diagnosis) = 17/173 (10%)

There may be many more people with depression (with high or low PHQs) who were unidentified because a SCID was not applied to the 780 and the screen depends wholly on the PHQ9 on a single application. At a typical (medium risk) prevalence rate of 20% there would be around 156 cases of depression in the group of 780 but in a high risk group where the prevalence may be 35% this would mean around 273 true cases. Just relying on a single application of the PHQ9 on its own (either by algorithm or recommended cut-off) is probably insufficient. Assuming (like the authors) that the sensitivity of the PHQ9 is a generous “0.88” (from the Kroenke J Gen Intern Med 2001;16:606–13 data) then there might be 33 missed cases in a high risk sample. However a meta-analysis from Wittkampf et al (General Hospital Psychiatry 2007; 29 388–395) found a pooled sensitivity of 0.77 and Gilbody (JGIM 2007 22;11: 1596-1602) found 0.81 (both in primary care) which would translate into 52 to 63 missed cases. Of course there is offset by the issue of false positives which should also be examined in a screening implementation study. However this remains speculation without the SCID data from the parent 780 sample which is not reported (but perhaps available to the authors?).

In summary I suggest this is genuinely useful paper about the hazards of screening implementation but it is not really about screening success for which a screening RCT or pre-post screen design is needed. A simple guide to interpretation of screening studies can be downloaded here http://www.psycho-oncology.info/education.htm
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Screening for depression in primary care setup

SHIVANAND KATTIMANI, Assistant Professor
03 June 2009



Many studies are being done in area related to depressive disorder. Depressive disorder is a common disorder still recognized uncommonly by people and by their physicians. The research article of Baas et al[1] is not unique but answer it has found is. These are the few shortcomings we noted in this research article: High risk groups defined by the authors are not valid high risk groups. Suggested high risk groups can be group with women gender, group with past or family history of mood depressive disorder, groups with substance abuse, groups belonging to lower socio-economic strata[2].

Group of patients with medically unexplained symptoms are likely to qualify more for somatoform disorders rather than depressive disorder. We are also not sure whether medically unexplained symptoms were actually unexplained based on clinical judgment of GP or following investigational protocol. It will be beneficial to know from which high risk group majority of MDD diagnosed patients came from. Concurrent validity between SCID-I and PHQ-9 needs discussion.

One year prevalence of MDD in general population is 5.28% 1 while in primary care setup it increases to 12%- 29% [3] [4]. Such low level of MDD identified in this study was not expected. Almost 50% did not respond to GP call letter, we are not sure how many of these actually were having MDD. It is well known that those who need the treatment most will not come forward to take it. When diagnosed people with MDD were asked to come for treatment nearly 50% refused. There has to be treatment options both pharmacological and nonpharmacological from which they can choose, as it is known that both can be equally effective[5] and patients with MDD might have certain negative attitudes towards pharmacological treatment [6] . It will be interesting know the reasons from these people who refused treatment.------------------------------------------------------------------------References: [1] Kim D. Baas, Karin A. Wittkampf, Henk C. van Weert, Peter Lucassen, Jochanan Huyser, Henk van den Hoogen, et al. Screening for depression in high-risk groups: prospective cohort study in general practice. Br J Psychiatry 2009;194:399-403.

[2] Hasin DS, Goodwin RD, Stinson FS, Grant BF. Epidemiology of major depressive disorder: results from the National Epidemiologic Survey on Alcoholism and Related Conditions. Arch Gen Psychiatry 2005;62:1097-1106.

[3] Pedrini E, Collazos Sanchez F, Qureshi A, Valero S, Ramos M, Revollo HW et al.Prevalence of major depression in Barcelona primary care settings: A comparative study between Latinos and native born patients. European Psychiatry 2009;24: Suppl(1),Page S669. 17th EPA Congress - Lisbon, Portugal, January 2009, Abstract book.

[4] Manote Lotrakul and Ratana Saipanish. Psychiatric services in primary care settings: a survey of practiotioners in Thailand. BMC Fam Pract 2006;7:48.

[5] Butler AC, Chapman JE, Forman EM, Beck AT. The empirical status of cognitive-behavioral therapy: a review of meta-analyses. Clin Psychol Rev 2006;26:17-31.

[6] Chakraborty K, Avasthi A, Kumar S, Grover S. Attitudes and beliefs of patients of first episode depression towards antidepressants and their adherence to treatment. Soc Psychiatry Psychiatr Epidemiol 2009;44:482-8.
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