Skip to main content
Full access
Letters to the Editor
Published Online: 1 December 2020

Lead-Time Bias as a Potential Explanation for the Link Between Duration of Untreated Psychosis and Outcome: Response to Iyer et al.

To the Editor: We appreciated the opportunity to read the thoughtful correspondence from Dr. Iyer and colleagues. They identified a number of factors that could have influenced our finding that the association between duration of untreated psychosis (DUP) and long-term outcome is explained by lead-time bias (1). We agree with two of the points put forward by Dr. Iyer and colleagues, and we analytically evaluate the effects of potential confounding variables mentioned in their letter.
First, as stated in our publication, the results of our analyses should not be interpreted as evidence that early intervention is ineffective or unnecessary. We wholeheartedly agree with Dr. Iyer and colleagues that early comprehensive intervention can provide meaningful symptom relief and short-term psychosocial benefits and is therefore tremendously valuable to patients, families, and society.
Second, we agree with Dr. Iyer and colleagues that the care received by the Suffolk County Mental Health Project cohort is not comparable to that delivered in early intervention clinical trials. Previous publications have shown that this cohort received inconsistent, primarily pharmacological care (2, 3). Indeed, Mojtabai’s review (3) of the Suffolk County and other clinical epidemiological cohorts concluded that only a minority of individuals with schizophrenia receive adequate evidence-based care. Comprehensive treatments, such as those delivered in coordinated specialty care programs, may have durable effects on illness course in schizophrenia. NAVIGATE (4), OnTrackNY (https://www.ontrackny.org), and a number of other early intervention programs show promise for greater efficacy. However, this cohort’s treatment is likely reflective of that received by patients in the general population, and our analyses show that such treatment was insufficient to halt psychosocial decline.
Although the Suffolk County cohort differs from clinical trial cohorts in many ways, we have no reason to believe that our findings are not generalizable. In two epidemiological cohorts from Scotland and Israel, both contemporary to the founding of the Suffolk County cohort, more than 90% of individuals with schizophrenia were eventually hospitalized (5, 6). Furthermore, despite significant declines in the availability of inpatient psychiatric beds in the years since the Suffolk County cohort was recruited, more than 75% of individuals in the Recovery After an Initial Schizophrenia Episode (RAISE) project were hospitalized prior to study entrance. Given these high rates, it is unlikely that our results were significantly affected by ascertainment of subjects during their first admission. Furthermore, the mean DUP in the Suffolk County sample (103 weeks) is within the range reported in a meta-analysis of epidemiological cohorts (10.4–213.2 weeks) (7), suggesting that this cohort is representative of the range of DUPs observed in the general population.
In contrast, clinical trial cohorts in mental health research generally have fewer comorbidities and less severe illnesses, and they are younger, have better functioning, and are of higher socioeconomic status than epidemiological cohorts (8). A comprehensive review of longitudinal studies of first-episode psychosis found that outcomes are substantially worse in representative samples (9). Importantly, the trajectory of participants in the Suffolk County project closely parallels that of population-representative studies, as reported in Menezes et al. (9). Therefore, although it is true that the Suffolk County cohort differs from clinical trial cohorts, it may reflect the modal course of schizophrenia for patients in the United States, most of whom will not be enrolled in clinical trials.
Dr. Iyer and colleagues cited evidence that the 90 days following first symptom onset may be a critical period during which intervention is effective in altering illness course. Figure 1 depicts a LOESS plot of trajectories as measured by the Global Assessment of Functioning Scale (GAF) as a function of DUP dichotomized at 90 days. The pattern of overlap between these groups is consistent with lead-time bias.
FIGURE 1. LOESS plot of trajectories as measured by the Global Assessment of Functioning Scale (GAF) as a function of duration of untreated psychosis (DUP) dichotomized at 90 days in a study of the association between DUP and illness course
Finally, it was suggested that attrition over time was a function of psychosocial function (as measured by the GAF) and that attrition may have biased the trajectories of psychosocial function. However, attrition in the present study was low. Excluding data missing because of mortality, only 10% of data points were missing. Furthermore, we estimated a pattern mixture model, the best statistical correction available for correcting nonignorable missing data (10), on GAF measures from baseline to the 20-year follow-up. After this correction, we found that the 20-year outcome worsened by less than 3 points on the GAF scale. The effect of DUP remained nonsignificant.
In sum, these analyses do not alter our findings that the association between DUP and long-term outcomes in schizophrenia is explained by lead-time bias. This does not mean that more robust treatments, such as those provided in early intervention clinical trials, cannot have lasting effects. However, determining whether this is true requires long-term follow-up of clinical trial cohorts and adjustment for lead time. Ultimately, even if the effect of early intervention is short-lived, we emphatically agree with Dr. Iyer and colleagues that these programs reduce suffering and are therefore valuable.

References

1.
Jonas KG, Fochtmann LJ, Perlman G, et al: Lead-time bias confounds association between duration of untreated psychosis and illness course in schizophrenia. Am J Psychiatry 2020; 177:327–334
2.
Mojtabai R, Herman D, Susser ES, et al: Service use and outcomes of first-admission patients with psychotic disorders in the Suffolk County Mental Health Project. Am J Psychiatry 2005; 162:1291–1298
3.
Mojtabai R, Fochtmann L, Chang S-W, et al: Unmet need for mental health care in schizophrenia: an overview of literature and new data from a first-admission study. Schizophr Bull 2009; 35:679–695
4.
Mueser KT, Penn DL, Addington J, et al: The NAVIGATE program for first-episode psychosis: rationale, overview, and description of psychosocial components. Psychiatr Serv 2015; 66:680–690
5.
Geddes JR, Kendell RE: Schizophrenic subjects with no history of admission to hospital. Psychol Med 1995; 25:859–868
6.
Weiser M, Werbeloff N, Dohrenwend BP, et al: Do psychiatric registries include all persons with schizophrenia in the general population? A population-based longitudinal study. Schizophr Res 2012; 135:187–191
7.
Penttilä M, Jääskeläinen E, Hirvonen N, et al: Duration of untreated psychosis as predictor of long-term outcome in schizophrenia: systematic review and meta-analysis. Br J Psychiatry 2014; 205:88–94
8.
Kennedy-Martin T, Curtis S, Faries D, et al: A literature review on the representativeness of randomized controlled trial samples and implications for the external validity of trial results. Trials 2015; 16:495
9.
Menezes NM, Arenovich T, Zipursky RB: A systematic review of longitudinal outcome studies of first-episode psychosis. Psychol Med 2006; 36:1349–1362
10.
Roy J, Daniels MJ: A general class of pattern mixture models for nonignorable dropout with many possible dropout times. Biometrics 2008; 64:538–545

Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 1181 - 1183

History

Accepted: 15 June 2020
Published online: 1 December 2020
Published in print: December 01, 2020

Keywords

  1. Psychosis
  2. Early Intervention
  3. Duration of Untreated Psychosis
  4. Epidemiology
  5. Treatment Delay
  6. First-Episode Psychosis

Authors

Affiliations

Katherine G. Jonas, Ph.D. [email protected]
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
Laura J. Fochtmann, M.D.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
Greg Perlman, Ph.D.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
Yuan Tian, M.Sc.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
John M. Kane, M.D.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
Evelyn J. Bromet, Ph.D.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).
Roman Kotov, Ph.D.
Department of Psychiatry and Behavioral Health (Jonas, Fochtmann, Perlman, Bromet, Kotov) and Department of Applied Mathematics and Statistics (Tian), Stony Brook University, Stony Brook, N.Y.; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Feinstein Institute for Medical Research, Manhasset, New York (Kane).

Notes

Send correspondence to Dr. Jonas ([email protected]).

Funding Information

The authors’ disclosures accompany the original article.

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

There are no citations for this item

View Options

View options

PDF/ePub

View PDF/ePub

Get Access

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - American Journal of Psychiatry

PPV Articles - American Journal of Psychiatry

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share