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Epidemiology:
doi: 10.1097/EDE.0b013e3182547094
Cancer

Psychiatric Disorder as a Risk Factor for Cancer: Different Analytic Strategies Produce Different Findings

Whitley, Elisea; Batty, G. Davida,b; Mulheran, Paul A.c; Gale, Catharine R.b,d; Osborn, David P.e; Tynelius, Perf; Rasmussen, Finnf

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Author Information

From the aDepartment of Epidemiology and Public Health, University College London, London, United Kingdom; bCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom; cDepartment of Chemical and Process Engineering, University of Strathclyde, Glasgow, United Kingdom; dMedical Research Council, Lifecourse Epidemiology Unit, Southampton, United Kingdom; eRoyal Free and University College Medical School, University College London, London, United Kingdom; and fDepartment of Public Health Sciences, Karolinska Institute, Stockholm, Sweden.

Submitted 24 August 2011; Accepted 26 January 2012; posted 6 April 2012.

David Batty has a Wellcome Trust Fellowship, which also supports Elise Whitley. The Centre for Cognitive Ageing and Cognitive Epidemiology is supported by the Biotechnology and Biological Sciences Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the MRC, and the University of Edinburgh as part of the cross-council Lifelong Health and Wellbeing initiative. Finn Rasmussen is funded by the Swedish Council for Working Life and Social Research. The authors reported no financial interests related to this research.

Correspondence: Finn Rasmussen, Child and Adolescent Public Health Epidemiology Group, Department of Public Health Sciences, Karolinska Institute, SE-17176 Stockholm, Sweden. E-mail: finn.rasmussen@ki.se.

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Abstract

Background: Reported associations between psychiatric disorders and cancer incidence are inconsistent, with cancer rates in psychiatric patients that are variously higher than, similar to, or lower than the general population. Understanding these associations is complicated by difficulties in establishing the timing of onset of psychiatric disorders and cancer, and by the possibility of reverse causality. Some studies have dealt with this problem by excluding patients with cancers predating their psychiatric illness; others have not considered the issue.

Methods: We examined associations between psychiatric hospitalization and cancer incidence in a cohort of 1,165,039 Swedish men, and we explored the impact of different analytic strategies on these associations using real and simulated data.

Results: Relative to men without psychiatric hospitalization, we observed consistent increases in smoking-related cancers in those with psychiatric hospitalizations, regardless of analytic approach (eg, hazard ratio = 1.73 [95% confidence interval = 1.52–1.96]). However, associations with cancers unrelated to smoking were highly dependent on analytic strategy. In analyses based on the full cohort, we observed no association or a modest increase in cancer incidence in those with psychiatric hospitalizations (1.14 [1.07–1.22]). In contrast, when men whose cancer predated their psychiatric hospitalizations were excluded, future cancer incidence was lower in psychiatric patients (0.72 [0.67–0.78]). Results from simulated data suggest that even modest exclusions of this type can lead to strong artifactual associations.

Conclusions: Psychiatric disorder–cancer incidence associations are complex and influenced by analytic strategy. A better understanding of the temporal relationship between psychiatric disorder and cancer incidence is required.

Psychiatric disorders are relatively common in the general population,1,2 and an extensive literature reports excess mortality among people with various types of mental disorder.2,3 Psychiatric patients also have a higher risk of specific physical illnesses, such as cardiovascular disease.4,5 These poor health outcomes may be because of worse health behaviors, for example, people with mental illness are more likely to smoke,6 be overweight,7 be less physically active,8 or have a poor diet.7,9,10 It has also been hypothesized that those with psychiatric disorders have worse access to healthcare,11 or that psychiatric staff (with whom these patients have most contact) is less efficient at diagnosing physical problems, particularly in the context of psychiatric comorbidities.12 On this basis, those with psychiatric disorders might also be expected to experience an excess risk of cancer incidence. However, despite numerous reports, associations between mental health and cancer incidence remain unclear. Studies have reported cancer experience in psychiatric patients that is variously worse than,13,14 similar to,15,16 or better than17,18 the general population. Two recent reviews of schizophrenia–cancer incidence associations5,19 have highlighted the high degree of heterogeneity across studies.

Many existing studies of psychiatric disorder and cancer incidence have important limitations. For example, many are based on follow-up of clinical samples, severely restricting generalizability; the majority focus on all cancers combined, limiting insights into etiologic processes; and often there is no distinction made between fatal and nonfatal cancers, for which risk factors may differ. Another challenge in interpreting the relationship between psychiatric disorders and cancer incidence is establishing the temporal relationship between exposure and outcome. Both diseases have potentially long induction periods, during which a person may have only minor symptoms, if any, making it difficult to establish the precise period “at risk.” In addition, evidence suggests that cancer patients have an excess of psychiatric disorders following their diagnosis,2022 particularly adjustment disorders and depression.20 This raises the problem of reverse causality, with cancer influencing the incidence of psychiatric illness rather than the converse. This temporal relationship has not been explored in detail, and studies that do consider the issue have dealt with it by excluding persons whose cancer predates their mental health diagnosis.18,23,24 However, this approach may be overly conservative when the exact time of onset of both conditions is in doubt.

The purpose of the present analyses, based on cohort and simulated data, was to (1) explore several analytic approaches used to examine the temporal relationship between psychiatric hospitalization and cancer incidence and (2) investigate whether apparently conflicting results in the literature are an artifact of analytic strategy.

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METHODS

The record linkage used to generate our study cohort has been reported previously.25,26 All nonadopted men born in Sweden between 1950 and 1976, with both biologic parents identified in the Multi-Generation Register, were identified and linked to the Population and Housing Censuses records (1960/1970), Military Service Conscription, Cause of Death, Cancer, and National Hospital Discharge Registers, resulting in 1,379,531 successful matches. Study approval was obtained from the Regional Ethics Committee, Stockholm.

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Data Linkage

Incident cancers for 1958–2004 were identified from the Swedish Cancer Register, a catalog regulated by law in which clinicians and pathologists record all new cancer cases. Analyses are based on first cancer registrations identified during follow-up. Individual cancers are distinct disease entities and do not have a single etiology. However, the aim of our study was to ascertain whether analytic strategy explains previously inconsistent cancer associations with psychiatric illness, and we therefore followed the approach taken in most previous studies by considering all cancers combined. In the context of psychiatric illness, smoking is likely to play an important role in explaining psychiatric disorder–cancer associations, and so we also explored the link between psychiatric illness and cancers considered to be related to smoking. Smoking-related cancers were defined as cancers of the lung, oral cavity, nasopharynx, oropharynx, hypopharynx, nasal cavity and paranasal sinuses, larynx, esophagus, stomach, pancreas, liver, kidney, ureter, urinary bladder, and uterine cervix, as well as myeloid leukemia27; the remaining cancers were considered unrelated to smoking.

Hospital admission data from 1969 to 2004 were based on the Swedish Hospital Discharge Register, which covered one-third of the Swedish population in 1970, 71% in 1977, and 100% from 1987 onward. The shortfall in the 1970–1980s occurred in counties of varying population density and socioeconomic composition, and there were no systematic differences in psychiatric hospitalization–cancer associations in counties included and not included in the register during these early years. From these data, we identified the earliest hospital admission for a psychiatric disorder during follow-up. Again, our aim was to investigate the role of analytic strategy, and our main analyses focused on all psychiatric hospitalizations combined. However, we also repeated analyses to investigate the impact of hospitalization for 6 specific disorders: schizophrenia, nonaffective psychosis, bipolar disorders, depressive disorders, neurotic and adjustment disorders, and personality disorders.

Childhood socioeconomic status (SES) was based on the highest occupation of either parent from the 1960/1970 Population and Housing Censuses. Population and Housing censuses records (1990) were used to ascertain adult SES, based on the study member's own occupation for those with an occupational code, and otherwise on household SES.

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Statistical Methods

Although cancer registration data were available beginning in 1958, psychiatric admission information was available only from 1969 onward, making identification of early psychiatric admissions in men born before 1969 problematic. The main analyses are therefore based on men who were examined at military service conscription in 1969–1994 at an average age of 18 years (range: 16–25). During these years, the law required this conscription examination; only men of foreign citizenship or with severe disability were excused.

After ascertaining that proportional hazards assumptions were not violated, we used Cox proportional hazards regression to explore psychiatric hospitalization–cancer associations. Follow-up began from the date of conscription and ended on the date of cancer registration, death, emigration, or 31 December 2004, whichever was first. Analyses were adjusted for year of birth, age at conscription, conscription center, childhood SES, and adult SES. Results presented here are based on all men with complete data, but we also explored associations after excluding men with cancer registrations or psychiatric admissions before conscription. We computed hazard ratios (HRs) and associated 95% confidence intervals (CIs).

Considering the inherent uncertainties regarding the timing of onset of both cancer and psychiatric events, we explored 3 analytic approaches. Method 1 followed the approach taken in previous studies that aimed to address the issue of reverse causality. Under this method, we excluded men whose first cancer registration predated their first psychiatric admission and then compared cancer incidence in men with at least 1 psychiatric admission during follow-up versus those with none. However, given the lag time involved in the identification of both cancer and psychiatric disorders, this approach may be overly conservative. Specifically, if a man had a preexisting (undiagnosed) psychiatric disorder when his cancer was diagnosed, then his exclusion would be inappropriate. In the current analysis, psychiatric disorders were identified from hospital admissions, which may have been some time after the actual onset of the disease. We therefore carried out 2 further analyses that included these men. In Method 2, we again compared men with psychiatric admission during follow-up versus those with none, but in this model, men whose cancer predated their first psychiatric admission contributed to analyses as “exposed” to psychiatric problems and having a “positive” outcome of interest (cancer), thus ignoring any impact of reverse causality. In Method 3, psychiatric admissions were entered as a time-dependent variable. In this model, men with psychiatric admissions were considered to have 2 periods of follow-up: (1) preadmission, during which they were “unexposed” and (2) postadmission, during which they were “exposed.” Men whose cancer registration followed their psychiatric admission contributed to analyses first as “unexposed-no cancer” and then as “exposed-cancer”; men whose cancer registration predated their psychiatric admission contributed once as “unexposed-cancer” and were censored before their first psychiatric admission.

To put our findings in the context of the published literature, we updated part of a previous meta-analysis19 of cancer incidence associations with schizophrenia, (the psychiatric diagnosis most widely studied in relation to cancer). We included all published studies of men who reported associations between schizophrenia and all cancers combined. We present separate results from studies that explicitly excluded preexisting cancers or cancers predating the identification of schizophrenia, and studies where no such statement was made. We also considered schizophrenia hospitalization–all-cause cancer associations in our cohort (1) based on all men and (2) after excluding men whose cancer predated their schizophrenia admission.

The 3 analytic strategies all have strengths and weaknesses and the most appropriate approach is unclear. We therefore carried out 2 series of Monte Carlo simulations to explore these issues in more detail. In the first, we simulated data with “cancer” and “psychiatric disorder” incidence rates and ages at “diagnosis” based on those in our cohort and with no association between the 2 conditions. We then compared results from the 3 analytic approaches. In the second, we carried out 10,000 repeated simulations with psychiatric and cancer incidence rates based on our cohort and no association between the two. However, rather than defining ages at diagnoses, we randomly excluded increasing proportions of subjects with both cancer and psychiatric disorder. For comparison with the majority of the published literature, we calculated standardized incidence ratios (SIR) as:

Equation (Uncited)
Equation (Uncited)
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with expected incidence equal to overall cancer incidence in our cohort. We recorded the number of datasets in which we observed an apparent reduction in cancer incidence associated with psychiatric disorder, determined by an upper 95% confidence limit of <100.

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RESULTS

Data Analyses

Of 1,379,531 men in the original cohort, 214,492 (16%) had missing data for at least 1 variable, leaving 1,165,039 men (84%) in our analytic sample. During an average 22 years of follow-up (range: 0–35), 65,243 men (6%) had at least 1 psychiatric hospital admission, 2419 (0.2%) developed a cancer related to smoking, and 13,322 (1%) developed a cancer unrelated to smoking. Men excluded from the analyses because of missing data were less likely to have had a psychiatric admission (1% in men excluded vs. 6% in men included in analyses) or to develop cancer (0.5% vs. 1.4%); however, unadjusted analyses including these men (not shown) were similar to those presented here, suggesting that selection bias was not an issue. Among men included in the analyses, 10,446 (1%) had a psychiatric admission and 1070 (0.1%) had a cancer registration before conscription; results from analyses excluding these men (not shown) were almost identical to those presented.

The mean age at first psychiatric admission was 31 (standard deviation = 8.3) and at first cancer registration was 37 (9.1) years. In total, 1314 (0.1%) men had both cancer registration (any site) and psychiatric admission. Of these, 410 had a cancer registration predating their first psychiatric admission. Although this is a small proportion (0.04%) of the full analytic sample, it is almost one-third of those with both psychiatric admission and cancer.

Associations of psychiatric admissions with smoking-related, nonsmoking-related, and all-cause cancer registrations are shown in Table 1. Regardless of the analytic approach, the risk of smoking-related cancers was consistently increased in men who had psychiatric admissions. After excluding men whose cancer predated their first psychiatric admission (Method 1), psychiatric hospitalization was associated with a 73% increase in smoking-related malignancies (unadjusted HR = 1.73 [95% CI = 1.52–1.96]). Standard and time-dependent Cox regression models that included men whose cancer predated their first psychiatric admission, produced associations that were slightly stronger, although there was little difference between Method 2 (2.03 [1.81–2.28]) and Method 3 (2.15 [1.90–2.44]). Adjustments for childhood and adult SES partially attenuated these associations.

Table 1
Table 1
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Analyses of cancers unrelated to smoking were based on a larger number of cases, and exclusions resulted in a larger proportion of losses from the group with both psychiatric admissions and cancer. In contrast to smoking-related cancers, psychiatric admission associations with nonsmoking-related cancers depended strongly on the analytic strategy. With Model 1, there was a marked reduction in nonsmoking cancers in men with a psychiatric admission (0.72 [0.67–0.78]). In contrast, analyses based on the full analytic sample showed a small increase in hazard (Model 2, 1.15 [1.07–1.22]); (Model 3, 1.06 [0.98–1.15]). Adjustments for SES in childhood and adulthood had no impact on associations.

Most previous studies have focused on all cancers combined. For comparison, we also present these results. Given the relative number of smoking- and nonsmoking-related cancers, it is not surprising that results for all cancers combined were similar to those for cancers unrelated to smoking. Analyses excluding men with cancers predating their psychiatric hospitalization (Method 1) were consistent with a decrease in risk (0.88 [0.83–0.94]), whereas analyses based on all men suggested a modest increase in risk (Method 2, 1.28 [1.21–1.36]; Method 3, 1.26 [1.18–1.35]).

Separate analyses of hospitalizations for schizophrenia, nonaffective psychosis, bipolar disorders, depressive disorders, neurotic and adjustment disorders, and personality disorders (not shown) were similar to those presented here. Associations with smoking-related cancers were consistent with an increase in hazard in those hospitalized for any of these mental disorders, regardless of analytic strategy. Results for nonsmoking cancers were dependent on analytic strategy; analyses that excluded cancers predating psychiatric hospitalization were consistent with a decrease in hazard in men with an admission for any of the 6 specific conditions, whereas analyses that included all men suggested that nonsmoking cancer incidence was similar or greater in those with condition-specific hospitalizations. The differences among analytic strategies were most marked for depression and neurotic and adjustment hospitalizations.

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Meta-analysis of Schizophrenia–cancer Associations

Altogether 6669 (0.6%) men in our analytic sample had at least 1 hospital admission for schizophrenia during follow-up, and 22 had a cancer predating this admission. For consistency with published studies, we present results for all cancers combined. Figure 1 shows schizophrenia hospitalization–cancer associations (with corresponding SIRs) from published studies that include and exclude men with a cancer preceding their schizophrenia hospitalization. There is considerable heterogeneity among published studies in terms of populations, exposures, and outcomes, and our classification is based only on reading the relevant article; exclusions may therefore have been made but not stated. However, results from our analysis based on the full cohort were consistent with those studies in which no exclusions were mentioned,14,28 all showing no association or a small increase in cancer incidence in psychiatric patients. Conversely, results from our analyses that excluded cancers occurring preschizophrenia hospitalization were strikingly consistent with studies in which these exclusions were also made18,23,24; all indicate a reduction of about 15% in cancer incidence among schizophrenia patients.

Figure 1
Figure 1
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Monte Carlo Simulations

Results from simulated data, with incidence and ages at diagnosis based on our cohort but with no association between psychiatric disorder and cancer, are shown in Table 2. Of 1,000,000 persons in the simulated data set, 56,203 had a psychiatric disorder, 13,970 had cancer, 789 had both, and 229 (0.02% of full sample; 29% of those with both diagnoses) had cancer predating psychiatric disorder. In analyses based on the full data set (Methods 2 and 3), HRs were, as expected, consistent with no association (1.01 [95% CI = 0.94–1.08] and 1.02 [0.94–1.11], respectively). However, analysis excluding cancers predating psychiatric disorder (Method 1) demonstrated a strong artifactual reduction in risk (0.71 [0.66–0.78]).

Table 2
Table 2
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Results from simulations in which proportions of those with both cancer and psychiatric disorders were randomly excluded are presented in Figure 2. The mean SIR calculated over repeated simulations is shown as a dashed line and, as expected, declines approximately in line with the percentage reduction. The proportions of simulations with an apparently protective effect are shown by solid lines separately for total population sizes of 1,000,000 and 100,000. Based on a psychiatric disorder rate of 5.6%, these population sizes correspond to between 5600 and 56,000 psychiatric patients and are broadly concordant with much of the published literature. Under the null hypothesis of no association, we would expect 2.5% of simulations to show a reduction in risk, and this is the case when no exclusions are made. However, as more persons are excluded, this proportion increases rapidly. Based on these simulations, we estimate that randomly excluding 5% of those with cancer and psychiatric disorder results in over a quarter of analyses with N = 1,000,000 and 4% of those with N = 100,000 demonstrating an artifactual protective effect. With 10% exclusions, these proportions rise to 79% and 9%, respectively, and the corresponding figures for 20% exclusions are 100% and 36%, respectively. When 30% are excluded, 100% of analyses with N = 1,000,000 and 78% of analyses with N = 100,000 show an artifactual protective effect.

Figure 2
Figure 2
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DISCUSSION

We have explored psychiatric hospitalization–cancer associations in a large cohort of >1 million Swedish men, with almost complete population coverage. Many previously published studies have focused on all cancers combined, and results have been inconsistent. It has been estimated that between one-quarter and one-third of cancers in men may be attributable to smoking,30 and this may be even lower in younger populations, such as those with psychiatric disorders. Results based on all cancers combined will therefore be dominated by nonsmoking cancers, and this may be misleading in practice. For example, in our data, smoking-related cancers were consistently more common in men with psychiatric admissions independent of analytic strategy, whereas associations with nonsmoking-related cancers were contradictory and highly dependent on the choice of model. However, for the purposes of discussion in the context of existing literature, we focus here on results for all cancers combined.

Our results demonstrate that the association of psychiatric admission and cancer incidence is sensitive to the analytic approach. Standard Cox regression analyses based on the full cohort (Method 2) were generally consistent with an increase in cancer incidence among those with psychiatric admissions. Results for schizophrenia were also consistent with published studies in which no statements regarding exclusions were made. However, given the potentially lengthy lags in the diagnosis of both psychiatric disorders and cancers, and the potential for psychiatric disturbance following a cancer diagnosis, analyses that ignore the possibility of reverse causality are likely to overestimate associations. Time-dependent Cox regression (Method 3) is a potentially useful approach in this situation. It is appropriate, however, only if the order of events is known explicitly. The gap between occurrence and identification of psychiatric disorders and also of cancers raises doubts about this assumption.

A more common approach is to exclude men whose cancer predates their psychiatric disorder (Method 1). Analyses of our cohort with this approach showed a marked reduction in cancer risk among those with psychiatric admissions. Schizophrenia associations with cancer were highly consistent with those from previous studies that also made these exclusions. A number of plausible biologic mechanisms explaining this apparent reduction in risk have been proposed and discussed in the literature. These include anticancer effects of antipsychotic/neuroleptic medications,31 genetic factors,19 later/poorer cancer detection in psychiatric patients,11,12 lower uptake in screening programs,32 or competing mortality.2,3

However, it is important to note that in our meta-analysis, the apparent reduction in cancer risk in psychiatric patients is specifically restricted to those studies in which exclusions were made. It is plausible that this analytic approach, designed to reduce the impact of reverse causality, overcompensates and leads to an artifactual reduction in risk. Results from our simulation study suggest that even modest exclusions of this type dramatically increase the probability of observing this artifactual risk reduction. This is particularly problematic when sample sizes are large, as is often the case in this context. A priori, we would expect analyses of the psychiatric disorders most commonly reported in cancer patients to be most affected by reverse causality. Depression and neurotic and adjustment disorders are the 2 disorders most commonly reported in patients with advanced cancers,20 and these were the 2 specific admissions for which the analytic strategy had the greatest impact in our results.

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Strengths and Limitations

The large size of our cohort offers higher statistical power and has allowed separate investigation of smoking-related cancers and cancers unrelated to smoking; this important distinction has not been widely made in previous studies. The longitudinal design has allowed direct comparison of psychiatric patients with the population from which they were drawn (in contrast with many previous studies based on follow-up of clinical samples), and has allowed the potential exclusion of psychiatric hospitalization arising as a result of a cancer diagnosis.

However, there are also a number of limitations. Our cohort consisted of young men at conscription, a strength in terms of psychiatric hospitalizations (which are more common in younger persons), but a limitation in terms of cancer development. (Despite lengthy follow-up, cohort members were a maximum of 55 years of age at end of follow-up). Moreover, data are restricted to men. We are unable to comment on the risk of cancer in women, which can have different etiologies.

We adjusted analyses for both childhood and adult SES. Although childhood SES clearly predates psychiatric and cancer events, adult SES may be influenced by psychiatric disorder or cancer diagnosis, and its inclusion may have led to overadjustment. In practice, adult SES had only limited impact on smoking-related cancer associations and no impact on nonsmoking-related cancer associations. We did not have extensive information on other factors (such as smoking or psychiatric medications), which might contribute to associations. The incompleteness of our smoking data is an important shortcoming, given the established associations with both psychiatric disorders and some cancers. Data on smoking status at conscription were available for a small subset (3%) of our study population, and in this subgroup, adjustment attenuated psychiatric hospitalization–smoking-related cancer associations. However, a single estimate of smoking status in early adulthood is not an accurate representation of life-long smoking experience. We may therefore have overestimated the link between psychiatric hospitalization and smoking-related cancers.

Finally, the use of hospital discharge data to identify psychiatric disorders while guaranteeing clinically identified problems, also limits results to problems severe enough to warrant hospital admission, whereas, for example, recent estimates suggest that 25% of nonaffective psychosis patients are treated as out-patients only.33 We identified men with mental illness severe enough to pose a danger to themselves, others, or both. More moderate mental health problems are likely to elicit associations with cancer that are lower in magnitude. Hospitalization rates also vary among psychiatric diagnoses; for example, persons with schizophrenia are more likely to be admitted to hospital than those with depression. However, it is reassuring that results for individual psychiatric diagnoses were similar to those for all diagnoses combined. The use of hospital admissions data also means that the age of onset of psychiatric disease may have been overestimated. This restriction will have no impact on analyses based on Method 2, which simply compared men with and without diagnosis, but may have led to additional exclusions in Method 1 and a longer “unexposed” period in Method 3, both of which may have exaggerated the impact of analytic strategy. However, it is clear from simulated data that even small exclusions have a marked impact on the results.

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Conclusions

The choice of analytic strategy has a strong impact on associations of psychiatric disorder with cancer incidence, which are complex and time-dependent. The exclusion of cancers predating psychiatric problems is common in this context, and may be reasonable if the timing of both events is clearly established. However, if psychiatric problems already exist but are not identified until after (or as a result of) cancer diagnosis, then these exclusions are not appropriate, and this approach may overcompensate. Moreover, this issue is not restricted to psychiatric disorder–cancer associations. Similar problems may arise whenever an association is based on exposures and outcomes that both have potentially long induction periods. Future exploration of these issues might include separate analyses of cause-specific cancers to reflect distinct etiology, better understanding of temporal relationships between psychiatric and cancer diagnoses, and development of appropriate methods for dealing with issues of reverse causality when the exact timing of events is unclear. The true nature of the association between psychiatric disorders and cancer should be established before further discussion of mechanisms.

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