Physical illness is strongly associated with depression and some 10-20% of general medical inpatients or outpatients have a depressive disorder. This is particularly marked for people with chronic disease where rates range from 11% of diabetics to 20% of people after a heart attack. Depression is a a risk factor for poor prognosis in physical disease, being associated with worse mortality, at least partly mediated via decreased adherence to treatment. Yet evidence shows that physically ill patients receive less antidepressant prescriptions than other depressed patients.
There are some specific challenges in recognising and treating depression in general medicine, early in an admission somatic symptoms of depression can difficult to distinguish from symptoms of physical illness and later on during treatment low mood can be considered 'understandable', with a natural resistance on the part of clinicians to medicalise normal emotional reactions. The inpatient environment is also unusual and stressful and it is unclear whether patients will maintain a low mood or improve when discharged home. Practically, the onset of antidepressants is generally believed to be delayed over two weeks which means that any effect may not be seen during an acute admission and psychological therapies such as CBT are just not available in general medicine.
In recent years the risks of self-harm and discontinuation syndromes with antidepressants have received significant coverage and since Irving Kirsch's 2008 paper much doubt has been raised about overall antidepressant efficacy in any other than the most severe patients. A recent Cochrane Review has addressed the question of antidepressant usage for depression in physically ill patients:
Rayner et al 'Antidepressants for depression in physically ill patients' Cochrane Database of Systematic Reviews 2010, Issue 3.
They looked at studies of depression quite broadly defined (major depressive disorder, adjustment disorder, dysthymia) and found 51 studies (mostly in SSRIs but also in tricyclics and a few less common antidepressants), with fluoxetine (Prozac) the drug most commonly studied (12 trials). The physical diseases studied included stroke (11 studies), HIV (7), Parkinson's disease (6), cancer (4), COPD (chronic bronchitis and emphysema; 3), diabetes (3) , heart attacks (2), and renal failure (2). At the two follow-up periods of most interest (6-8 wks and 9-18 wks) there were around 1,000-1,500 subjects included in the analysis.
Looking at other aspects they found that there were more people dropped out of the study from the antidepressant group than the placebo group (this was marginally significant) with an odds-ratio of 1.3 (95% confidence interval 1.0-1.8). Looking at side-effects, dry mouth and sexual dysfunction were both significantly more likely to be reported by those in the antidepressant group, the latter being primarily driven by those taking SSRIs. So overall antidepressants had side-effects sufficiently bad to lead more people to drop out of the study.
The study didn't find any striking differences between the efficacy of SSRIs and other antidepressants, nor differences between taking a narrow (major depressive disorder only) or broad definition of depression.
Looking at the I-squared statistic for trial hetrogeneity we can see that for dichotomous outcomes differences between trials were not very large but for the mean difference outcomes there was very large heterogeneity. However, this seems to be due to two studies with stonkingly big effect sizes (improvements greater than 10 points on the HRSD) and excluding these from analyses drops the I-squared right down without massively affecting the results.
Overall this is quite an interesting finding and it suggests that antidepressants can be really very effective for depression in physically ill patients. But there are some limitations to bear in mind:
- Most studies were pretty small, almost all with less than 100 subjects and we know that small studies are more likely to overestimate the size of the beneficial effect
- Trial quality was actually pretty low, and low quality trials are known to overestimate effect sizes (more on this below)
- Publication bias was apparent in the studies (more below)
- The effect of baseline severity has become a hot topic since Kirsch et al and this study didn't look at this (more below)
- They looked only at the 10 most common side-effects but not overall adverse event rates, or specifically serious adverse events, and this prevents detection of less common but serious complications (stuff like death or suicide)
- No subgroup analyses were performed to see if antidepressants were more effective in specific physical illnesses (say in stroke rather than HIV)
- They did not look at studies with co-morbid psychiatric illness, this is important because mixed disorders, particularly with aspects of both depression and anxiety, are very common
Trial quality was disturbingly low, the authors used the 'Risk of Bias' table from the Cochrane Handbook to score as 'low risk', 'unclear risk', or 'high risk' of bias on six items:
- Sequence generation
- Allocation concealment
- Incomplete outcome data
- Selective outcome reporting
- Other issues
Kirsch et al and its widespread impact is curious. Kirsch et al, looking at the same FDA data as Turner et al, found that the NICE threshold for 'clinical significance' (an improvement of 3 points on the HRSD or 0.5 SMD) was reached around a baseline severity (as measured by the HRSD) of 26 points, which is classified as 'very severe' by NICE and the American Psychiatric Association (see right). Similar results were found by Fournier et al looking at individual subject level data.
Kirsch et al it seems most likely that this disparity is due to publication bias in the Cochrane meta-analysis. There are some interesting issues regarding the way that studies in general depression usually have a more severe major depression population and any extrapolation to less severe patients is on the basis of few studies whereas the Cochrane review includes a number of less severe conditions and it is possible that this makes it therefore more sensitive to beneficial effects at the lesser degrees of severity. It is also possible that physically ill patients may be more responsive to antidepressants but I'm unconvinced.
This study looked at largely outpatient populations with chronic illness and it isn't clear whether the results are directly applicable to inpatient populations but it certainly supports the use of antidepressants in inpatient depression and suggests that at the very least they are likely to be as effective in this population as in the general population of depressed patients.
Finally it is worth noting that NICE has a guideline on treating depression in chronic physical illness which makes recommendations which are broadly similar to those they make for depression in general:
- For low persistent subthreshold depressive symptoms or mild to moderate depression:
- Low intensity psychosocial intervention (e.g. computerised CBT etc.)
- If symptoms persist, previous severe depression, or symptoms compromising care consider either:
- SSRI (citalopram or sertraline first line)
- High intensity psychosocial intervention (e.g. individual CBT etc.)
- Severe depression
- Antidepressant and individual CBT
- Be aware of drug interactions
* Standardised mean difference is the difference between the mean outcome scores for the antidepressant and placebo groups divided by the standard deviation, this corresponds to something like a difference of 4 points on the HRSD. Since many studies don't report dichotomous 'improvement' measures, or use different definitions, and these have to be 'imputed' using the mean difference data (making assumptions about how the data is distributed), I prefer mean difference data, ideally using the raw HRSD figures rather than the standardised mean difference (since this can create odd distortions in the data, e.g. in Kirsch et al's study). Almost all studies use the original 17-item HRSD but the few studies that instead use, say, the Montgomery-Åsberg Depression Rating Scale means that the authors have used the SMD so that this data can be combined (the SMD is supposed to allow you to combine data from different scales that are intended to measure the same thing).
** This data should be free from publication bias because the FDA legally mandates the pharmaceutical companies to supply all studies performed on the drug.
*** Cochrane actually discourage adding these up to produce a scale but I can't think of a better way to see which studies are more or less biased.
**** Only including those studies with HRSD data, and those trials where I could access the article and extract it. Since I didn't try too hard to check everything it is quite possible some scoring from scales other than the 17-item HRSD crept in there.
In response to neuroskeptic in the comments, here's the baseline severity data split by antidepressant and placebo groups (as seen in Kirsch et al's analysis), the regression is weighted by sample size, the baseline severity is mean HRSD score, the improvement is mean baseline severity minus mean HRSD score at 6-8 weeks. We can see that increasing baseline severity leads to increasing response to antidepressant with placebo response fairly flat. This was pretty much what we found when we looked at HRSD outcome data from the Kirsch et al study.