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First Published Online July 31, 2009
The Oncologist, Vol. 14, No. 8, 806-813, August 2009; doi:10.1634/theoncologist.2008-0285
© 2009 AlphaMed Press

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Epidemiology and Community Health

Survival Expectations of Patients Diagnosed with Hodgkin's Lymphoma in 2006–2010

Hermann Brennera, Adam Gondosa, Dianne Pultea,b

aDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; bWeill Cornell Medical Center, New York, New York, USA

Key Words. Cancer registries • Hodgkin's lymphoma • Prognosis • Survival

Correspondence: Hermann Brenner, M.D., M.P.H., Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Bergheimer Str. 20, D-69115 Heidelberg, Germany. Telephone: 49-6221-548140; Fax: 49-6221-548142; e-mail: h.brenner{at}dkfz-heidelberg.de

Received December 22, 2008; accepted for publication June 28, 2009; first published online in THE ONCOLOGIST Express on July 31, 2009.

Disclosures: Hermann Brenner: None; Adam Gondos: None; Dianne Pulte: None.

The content of this article has been reviewed by independent peer reviewers to ensure that it is balanced, objective, and free from commercial bias. No financial relationships relevant to the content of this article have been disclosed by the authors or independent peer reviewers.


    ABSTRACT
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
Available long-term survival figures for patients with Hodgkin's lymphoma (HL) from population-based cancer registries mostly refer to patients diagnosed in the 1980s and 1990s, and do not reflect recent progress in and spread of effective therapy at the population level. Using data from the Surveillance, Epidemiology, and End Results program, we employed a novel model-based projection method to estimate 5- and 10-year relative survival expectations of HL patients in the U.S. diagnosed in 2006–2010. Preliminary empirical evaluation of the method using historical data indicates excellent performance. Projections of 10-year relative survival percentages and their standard errors by age groups are as follows: 15–24 y: 94.7 (1.1), 25–34 years, 89.4 (1.5); 35–44 years, 90.1 (1.6); 45–54 years, 83.6 (2.7); 55–64 years, 70.5 (4.7); 65–74 years, 48.5 (5.9); and 75+ years, 24.0 (5.7). These estimates are 2.5–11.1 percentage points higher than those obtained by standard cohort analysis from the same database (pertaining to patients diagnosed in 1991–1995). Patients diagnosed with HL in 2006–2010 have higher long-term survival expectations than suggested by conventional survival statistics from population-based cancer registries. The 10-year survival expectations are now close to or exceed 90% in all age groups up to age 45, and exceed 80% and 70% in the 45–54 and 55–64 age groups, respectively.


    INTRODUCTION
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
Since the breakthroughs in combination chemotherapy for patients with Hodgkin's lymphoma (HL) starting in the 1960s, the prognosis for patients has been rising dramatically. Although the greatest increase in survival occurred between the 1960s, when the 5-year survival rates were well below 10%, and the early 1980s [1], improvements have been steadily ongoing since then at the population level, probably as a result of enhanced spread of therapeutic innovations. According to a recent period analysis from the Surveillance, Epidemiology, and End Results (SEER) program, the 5-year relative survival rate for HL patients across all age groups in the U.S. steadily increased from 73.5% to 85.2%, and the 10-year relative survival rate increased from 62.1% to 80.1% between 1980–1984 and 2000–2004 [2]. The increase was particularly pronounced for the 45–59 and 60+ age groups, who nevertheless continued to have considerably lower survival expectations than younger patients. Although this period analysis provided more up-to date estimates of long-term survival than previous studies that had mostly relied on cohort estimates of survival for patients diagnosed in the 1980s and 1990s, period analysis still relies partially on data from patients diagnosed many years ago and treated with regimens that may now be outmoded, and is therefore still not reflective of the survival expectations of patients diagnosed currently. Therefore, the long-term survival expectations of currently diagnosed HL patients are expected to be even higher as a result of continued improvement and spread of effective therapy.

One major obstacle in deriving truly up-to-date estimates of long-term survival at the population level is the delay in availability of cancer registry data, which is typically in the range of several years, even in the best cancer registries in the world. For example, the most recent cancer registry data from the SEER program are typically available approximately 3 years after the last calendar year included in the database [3]. With further delay in analysis and publication, survival analyses from these data are typically available only ≥5 years after the last calendar year included. To overcome the delay resulting from availability, analyses, and reporting of cancer registry data, model-based projections of long-term survival have recently been proposed [4]. An empirical evaluation using data from the Finnish Cancer Registry showed this approach to provide up-to-date and accurate data on long-term cancer survival even with the common delay in cancer registration. However, no evaluation or application for patients with HL has been reported to date.

The aim of this study was to derive estimates of long-term survival expectations for patients with HL diagnosed in 2006–2010 using model-based projection, after thorough empirical evaluation of the performance of this method.


    MATERIALS AND METHODS
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
All data presented in this paper are derived from the 1973–2005 limited-use database of the SEER program of the U.S. National Cancer Institute issued in April 2008 [5]. Data included in the 1973–2005 SEER database are from population-based cancer registries in Connecticut, New Mexico, Utah, Iowa, Hawaii, Atlanta, Detroit, Seattle-Puget Sound, and San Francisco-Oakland, which together cover a population of about 30 million people.

For this analysis, we selected 20,879 patients aged ≥15 years with a first diagnosis of HL (and no previous cancer diagnosis) between 1973 and 2005, who had been followed for vital status until the end of 2005. After exclusion of 69 patients (0.3%) who were reported by autopsy only and 75 patients (0.4%) who were reported by death certificate only, there remained 20,735 patients (99.3%) for the survival analysis.

Empirical Evaluation of the Projection Approach
In the first step, we empirically evaluated the performance of the model-based projection approach compared with traditional cohort and period analyses to derive up-to-date survival estimates using historical data. The principle of this evaluation is illustrated in Figure 1. First, we calculated the 5-year survival rate actually observed for patients diagnosed in 1996–2000, that is, the most recent cohort of patients for whom a 5-year follow-up was complete by the end of 2005, the closing year of incidence and follow-up in the SEER 1973–2005 database (Fig. 1, upper block). Next, we compared the 5-year survival rate of this cohort with the most up-to-date estimates of the 5-year survival rate that might have been obtained in 1996–2000, that is, at the time of diagnosis of this cohort, by the following methods of survival analysis.


Figure 1
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Figure 1. Schematic illustration of data used to calculate the 5-year relative survival rate actually observed for patients diagnosed in 1996–2000 and of data that could have been used for deriving "up-to-date" estimates of the 5-year relative survival rate in 1996–2000 by the various methods.

 
With traditional cohort analysis (Fig. 1, second block), the most recent estimate of the 5-year survival rate available in 1998, the mid-year of diagnosis of the 1996–2000 cohort, would have pertained to patients diagnosed in 1986–1990 and followed up to 1995 (assuming a similar "delay" in availability of cancer registry data in 1998 as in 2008, and ignoring a further delay resulting from the time needed for statistical analyses and reporting of results).

With period analysis (Fig. 1, third block), an estimate of the 5-year survival rate exclusively reflecting the survival experience of patients in 1991–1995 could have been obtained in 1998, which would have been derived from patients diagnosed in 1986–1995. Period analysis, first introduced by Brenner and Gefeller in 1996 [6], has been shown by extensive empirical evaluation to quite closely predict 5-year survival rates later observed for patients diagnosed in the respective period [7, 8].

With the projection approach (Fig. 1, bottom block), the numbers of deaths and numbers of persons at risk for single years following diagnosis would first have been derived separately for each of the periods 1981–1985, 1986–1990, and 1991–1995. Then, a generalized linear regression model with binomial error structure would have been fitted, with the proportion of survivors among persons at risk as the dependent variable, years following diagnosis as a categorical predictor variable, and grouped years of follow-up (categories: 1981–1985, 1986–1990, and 1990–1995) as a numerical predictor variable. This model estimates a linear trend in the follow-up year–specific survival rates from the periods 1981–1985 to 1991–1995 and can be used to project follow-up year–specific survival in 1996–2000, assuming continuation of this trend. A detailed description of this modeling approach is given elsewhere [4] (the only difference in the approach applied in this analysis is the use of a binomial rather than a Poisson regression model).

We then calculated the difference between the 5-year survival rate estimates obtained with each approach and the 5-year survival rates later observed for patients diagnosed in 1996–2000. Analogous calculations were done for cohorts of patients diagnosed in 1995–1999, 1994–1998, and 1993–1997, that is, all 5-year cohorts of patients for whom such analyses could be carried out with the SEER-9 1973–2005 database. All analyses were carried out for all age groups combined, as well as separately for the following seven age groups: 15–24, 25–34, 35–44, 45–54, 55–64, 65–74, and 75+.

Application of the Modeling Approach to Project Survival in 2006–2010
In the second step, the projection approach was employed to project the 5-year survival rate as well as the 10-year survival rate in 2006–2010. Note that preliminary empirical evaluation of the projection approach for the 10-year survival rate was not possible because it would have required an even longer time series of data than what is available in the SEER-9 1973–2005 database. Again, the most up-to-date estimates of the 5- and 10-year survival rates available from traditional cohort analysis, pertaining to cohorts of patients diagnosed in 1996–2000 (5-year survival rate) or 1991–1995 (10-year survival rate) and period analysis (pertaining to the calendar period 2001–2005), were calculated for comparison.

According to standard practice in population-based cancer survival analysis, relative rather than absolute survival rates were calculated in all analyses. Relative survival rates reflect the survival of cancer patients compared with the survival of the general population [9, 10]. The latter was derived according to the so-called Ederer II method [11] from U.S. sex-, age-, and race-specific life tables [12].

All analyses were performed with the SAS software package, version 9.1 (SAS Institute Inc., Cary, NC) using appropriate adaptations of previously described macros for standard period analysis and model-based projections [4, 13].


    RESULTS
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
Of the 20,735 patients included in this analysis, about one quarter were 15–24 years old and another quarter were 25–34 years old at the time of diagnosis (Table 1). The older age groups included much lower numbers of patients.


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Table 1. Numbers of cases diagnosed with Hodgkin's lymphoma according to age

 
Overall, the 5-year relative survival rate observed for cohorts of patients diagnosed in 1993–1997, 1994–1998, 1995–1999, and 1996–2000 gradually increased from 82.7% to 84.6% (Table 2, Observed column, age 15+). The 5-year relative survival rate was consistently >90% in the 15–24 and 25–34 age groups, and between 80% and 90% in the 35–44 and 45–54 age groups. Survival was much lower and strongly decreased with age among older patients.


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Table 2. Comparison of the 5-year relative survival rates later observed for cohorts of patients diagnosed with Hodgkin's lymphoma in various 5-year calendar periods and the most up-to-date estimates of the 5-year relative survival rates potentially available during these 5-year periods from cohort analysis, period analysis, or model-based projections

 
With just one exception, the most up-to-date estimates of the 5-year relative survival rate potentially available in the years of diagnosis of these cohorts from cohort or period analysis were always lower, with differences being more pronounced for older age groups (Table 2). The mean difference (range) from the later observed 5-year relative survival rate was –7.1 percentage points (–15.8 to –2.8) for the cohort analysis and –4.9 percentage points (–11.4 to 1.5) for the period analysis. Although the majority of the 5-year relative survival rate estimates obtained from model-based projections were also pessimistic (as indicated by the negative signs of the differences), differences from the later observed 5-year relative survival rates were typically much smaller, with a mean value of –1.3 percentage points (range, –5.2 to 9.0, with the latter being a single outlier). In 30 of 32 cases, the model-based estimates were the estimates that came closest to the later observed 5-year relative survival rates (grey shaded cells in Table 1). The standard errors of the 5-year relative survival rates were very similar for the cohort and period estimates, but typically about 30% larger for the model-based projections.

Application of the modeling approach to project survival in 2006–2010 yielded 5- and 10-year relative survival rate estimates that were, in most cases, higher than the most-up-to-date survival rate estimates obtained by period analysis (pertaining to the 2001–2005 period) or cohort analysis (pertaining to the cohort of patients diagnosed in 1996–2000 in the case of the 5-year survival rate and to the cohort of patients diagnosed in 1991–1995 in the case of the 10-year survival rate) (Table 3). Overall, differences were more pronounced for the 10-year relative survival rate (82.6% versus 80.4% and 76.3%) than for the 5-year relative survival rate (86.7% versus 85.2% and 84.6%). According to the projection, the 10-year relative survival expectations of patients diagnosed in 2006–2010 are close to or exceed 90% in all age groups up to 45 years of age, and still exceed 80% and 70% in the 45–54 and 55–64 age groups, respectively. In most cases, the most up-to-date estimates available from traditional cohort analysis and period analysis are lower, with differences ranging up to –11.1 and –6.6 percentage points for the cohort analysis and period analysis, respectively. Patterns seemed to be different in the oldest age group, but need to be interpreted with caution, given the large standard errors for the survival estimates in that group.


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Table 3. Most up-to-date estimates of the 5-year and 10-year relative survival rates of patients diagnosed with Hodgkin's lymphoma obtained by different methods

 
As Figure 2 illustrates, the differences between projections and cohort estimates are largest in the 45–54 and 55–64 age groups, suggesting that the previously observed strong age gradient in prognosis over this age range has been substantially reduced in recent years.


Figure 2
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Figure 2. Projected 5- and 10-year relative survival rates by age for patients diagnosed in 2006–2010 (solid lines) compared with patients diagnosed in 1996–2000 and 1991–1995, respectively. Patients with Hodgkin's lymphoma, Surveillance, Epidemiology, and End Results SEER-9 database, 1973–2005.

 

    DISCUSSION
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
To our knowledge, this is the first application of model-based projection to provide detailed estimates of survival expectations by major age groups for concurrently diagnosed HL patients. Based on very encouraging results from empirical evaluation of the method using historical data, model-based projection was employed to derive expected 5- and 10-year relative survival rates of HL patients diagnosed in the U.S. in 2006–2010. Our projections reveal that the 10-year relative survival expectations have reached levels of about 95% for patients aged 15–24 years, 90% for 25- to 44-year-old patients, and >80% and 70% for 45- to 54-year-old and 55- to 64-year-old patients, respectively. For only the relatively small groups of patients aged ≥65 years, the 10-year relative survival expectations remain much lower, at levels <50%.

The survival rates of patients with a diagnosis of HL in 2006–2010 projected in this study are substantially higher than previously available survival estimates, many of which still refer to patients diagnosed and treated in the 1990s [14, 15]. They are also higher than the few available period estimates for the beginning of the 21st century from a previous analysis from our group and a recent report from the EUROCARE-4 study [2, 16]. For example, using a period analysis for the years 2000–2002, the 5-year relative survival rate for all ages combined was 81.4% in European countries. The 5-year relative survival rate in the SEER-13 database for the same time period was calculated as 80.6%, and no estimates of the 10-year relative survival rate were provided [16].

Clearly, the validity of our projections depends on whether and to what degree the implicit assumption holds that the previously observed steady upward trend in survival has continued in the most recent years. Given the steady improvement seen in previous decades, the projection method showed excellent performance in the empirical evaluation, and, with two exceptions, consistently provided more up-to-date and more valid estimates of long-term survival than traditional cohort analysis and also standard period analysis [6, 13]. The only major failure of the projection occurred in one of the analyses for the oldest age group, possibly because of random variation, given the large standard errors of the survival estimates in this comparably small group.

Within previous decades, improvements in radiation therapy, chemotherapy, and stem cell transplantation have been the driving forces behind the improvement in survival. Over the past several decades, the use of combination chemotherapy and improvements in this therapy have contributed greatly to increasing survival rates for patients with HL [17, 18]. Additionally, the use of high-dose salvage chemotherapy and hematopoietic stem cell transplantation in relapse has contributed to improvements in survival [19]. Survival has continued to rise since the 1990s, even though there has been only incremental therapeutic improvement and there has been a shift in focus from the implementation of even more effective therapy to the implementation of equally effective, but less toxic, therapy, such as the use of smaller radiation fields, which have been demonstrated to reduce toxicity without reducing treatment efficacy [20]. A possible explanation for the ongoing increase in survival in population-based analyses despite limited therapeutic improvement could be the more widespread use of effective therapy. In particular, the observed catch-up of older patients with respect to survival expectations may reflect both the increased use and less toxicity of new therapeutic regimens among older patients, and increased use of high-dose therapy and hematopoietic stem cell transplant in patients into the 6th and 7th decades of life. In addition, more refined diagnostic techniques, especially in older age groups, and better staging techniques may also have contributed to longer survival. Given the very high levels of survival currently achieved in younger patients, with a 10-year relative survival rate ≥90%, less room is left for any further increase in survival in these age groups, and limiting adverse sequelae of therapy in terms of quality of life, second malignancies, and comorbidity may even become more important. Among older patients, however, despite the recent catch-up, there remains a large potential for coming closer to the very high survival rates currently observed for younger patients.

In the interpretation of our data, a number of limitations have to be kept in mind. Given the limited data on therapy included in the SEER database, direct assessment of the impact of changes in therapy on survival is not possible. Even the long time series of data included in the SEER database, currently 1973–2005, was insufficient to carry out empirical evaluation of projections of the 10-year survival rate in the same way as was done for the 5-year survival rate. There is no obvious reason why the method should be less useful for the 10-year survival rate than for the 5-year survival rate. However, as previously shown for estimates of the 10-year survival rate obtained by standard period analysis [7, 8], the projections of the 10-year survival rate (obtained by extrapolation of trends in period estimates) are still expected to be somewhat too pessimistic in cases of ongoing improvements in survival. Finally, keeping long-term morbidity and mortality from second cancers and other potential late effects of therapy in mind, extension of the projections to longer-term survival estimates, such as 15-, 20-, or 25-year survival rates, is desirable, but would require even longer time series of population-based cancer registry data.


    CONCLUSIONS
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
In summary, despite its limitations, our analysis indicates that the long-term survival expectations of currently diagnosed patients with HL are likely to be substantially higher than those suggested by previously available survival statistics. This encouraging news should be disclosed to patients, clinicians, researchers, and health authorities in a timely manner, and the projection approach applied here may make a major contribution to this end. Disclosing the more optimistic up-to-date survival figures may help prevent patients from being unnecessarily burdened by potentially outdated survival statistics. Timely disclosure of these figures to health authorities may help to ensure the necessary support for delivery and further development of effective treatment regimens.


    AUTHOR CONTRIBUTIONS
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
Conception/Design: Hermann Brenner

Data analysis: Hermann Brenner, Adam Gondos, Dianne Pulte

Manuscript writing: Hermann Brenner

Final approval of manuscript: Hermann Brenner, Adam Gondos, Dianne Pulte


    ACKNOWLEDGMENT
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 
Dianne Pulte was supported by a visiting scientist scholarship from the German Cancer Research Center.


    REFERENCES
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Author Contributions
 References
 

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  3. Surveillance, Epidemiology, and End Results (SEER) Program. Limited-Use Data (1973–2004), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2007, based on the November 2006 submission. Available at http://www.seer.cancer.gov. accessed July 23, 2009.
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  5. Surveillance, Epidemiology, and End Results (SEER) Program. Limited-Use Data (1973–2005), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2008, based on the November 2007 submission. Available at http://www.seer.cancer.gov. accessed December 15, 2008.
  6. Brenner H, Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer 1996;78:2004–2010.[CrossRef][Medline]
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  8. Brenner H, Hakulinen T. Up-to-date long-term survival curves of patients with cancer by period analysis. J Clin Oncol 2002;20:826–832.[Abstract/Free Full Text]
  9. Ederer F, Axtell LM, Cutler SJ. The relative survival rate: A statistical methodology. Natl Cancer Inst Monogr 1961;6:101–121.[Medline]
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  13. Brenner H, Gefeller O, Hakulinen T. Period analysis for 'up-to-date' cancer survival data: Theory, empirical evaluation, computational realisation and applications. Eur J Cancer 2004;40:326–335.[CrossRef][Medline]
  14. Allemani C, Sant M, De Angelis R et al. Hodgkin disease survival in Europe and the U.S.: Prognostic significance of morphologic groups. Cancer 2006;107:352–360.[CrossRef][Medline]
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  16. Verdecchia A, Francisci S, Brenner H et al. EUROCARE-4 Working Group. Recent cancer survival in Europe: A 2000–2002 period analysis of EUROCARE-4 data. Lancet Oncol 2007;8:784–796.[CrossRef][Medline]
  17. Canellos GP, Anderson JR, Propert KJ et al. Chemotherapy of advanced Hodgkin's disease with MOPP, ABVD, or MOPP alternating with ABVD N Engl J Med 1992;327:1478–1484.[Medline]
  18. Diehl V, Franklin J, Pfreundschuh M et al. Standard and increased-dose BEACOPP chemotherapy compared with COPP-ABVD for advanced Hodgkin's disease. N Engl J Med 2003;348:2386–2395.[Abstract/Free Full Text]
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  20. Behringer K, Diehl V. Twenty-five years clinical trials of the German Hodgkin Study Group (GHSG). Eur J Haematol 2005;(66) (Suppl):21–25.



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