Model-based Period Analysis Research Articles

Up-to-date results on survival of patients with melanoma in Germany

Prior analyses of survival of patients with primary cutaneous malignant melanoma from Germany were based only on small populations and need to be updated. We give a detailed overview of relative 5-year survival by sex, age group, histology, tumour stage and body site, and of time trends in a population of 33 million (40% of Germany), and compare survival in the federal states. Conventional and model-based period analysis using the Ederer II method was applied to patients with melanoma diagnosed during 1997-2006 in Germany to assess 5-year relative survival (RS) rates and time trends. In total, 37,155 melanoma cases were included. Overall age-adjusted 5-year RS for the time period 2002-2006 was 91·9% for women and 87·0% for men. Survival differences by age group, histology, tumour stage and body site were found. No significant overall trend (2002-2006) was seen either in women or in men. Differences in survival between federal states were small; no clear pattern was seen. Based on the most recent and high-quality data from population-based cancer registries a comprehensive picture on melanoma survival in Germany was given. Survival from cutaneous malignant melanoma was high compared with other cancer sites and did not change during the analysed period 2002-2006. Patterns in melanoma survival by sex, age, tumour stage, histology and body site were in good agreement with previously published findings. No relevant differences between federal states were found.

Survival of endometrial cancer patients in Germany in the early 21st century: a period analysis by age, histology, and stage

BackgroundPopulation-based studies on endometrial cancer providing survival estimates by age, histology, and stage have been sparse. We aimed to derive most up-to-date and detailed survival estimates for endometrial cancer patients in Germany.MethodsWe used a pooled German national dataset including data from 11 cancer registries covering a population of 33 million people. 30,906 patients diagnosed with endometrial cancer in 1997-2006 were included. Period analysis was performed to calculate 5-year relative survival (RS) in 2002-2006. Trends in survival between 2002 and 2006 were examined using model-based period analysis. Age-adjustment was performed using five age groups (15-44, 45-54, 55-64, 65-74, and 75+ years).ResultsOverall, age-adjusted 5-year relative survival in 2002-2006 was 81%. A moderate age gradient was observed, with 5-year RS decreasing from 90% in the age group 15-49 years to 75% in the age group 70+ years. Furthermore prognosis varied strongly by histologic subtypes and stage, with age-adjusted 5-year RS ranging from 43% (for sarcoma) to 94% (for squamous metaplasia), and reaching 91% for localized, 51% for regional, and 20% for distant stage. Except for age group 65-74 years, no significant improvement in survival was seen during the recent 5-year period under investigation.ConclusionIn this comprehensive population-based survival analysis of patients with endometrial cancer from Germany, prognosis of endometrial cancer moderately varied by age, and strongly varied by histology and stage. While prognosis is rather good overall, further improvement in 5-year relative survival of endometrial cancer patients has been stagnating in the early 21st century.

Population Level Survival for Patients with Multiple Myeloma: Variation and Growing Disparity for Patients of Minority Race or Ethnicity

Abstract 3126 BackgroundSurvival for patients with multiple myeloma has increased during the first decade of the 21st century, especially in people diagnosed at a younger age. It is currently unknown whether the improvements in survival have extended equally to people of minority ethnic and racial groups. A recent publication found higher incidence and lower survival for AA versus whites. However, the above publication did not include detailed data on changes in survival in different time periods and little data is currently available for the Hispanic or Asian population. Here, we examine changes in survival in patients with myeloma by racial and ethnic group. MethodsUsing cancer registry data from the Surveillance, Epidemiology and End Results Program (SEER9), we assessed trends in 5-year relative survival for patients with multiple myeloma by racial and ethnic group, including non-Hispanic whites (nHw), African-Americans (AA), Hispanics, and Asian-Americans (Asian) for the periods 1993–97 and 2003–07. Model-based period analysis was used to obtain the most up-to-date measurements of survival. Age adjusted analysis was performed using age-standardized survival with age adjustment according to the International Cancer Survival Standard. ResultsOverall, five-year relative survival improved for the time periods studied. Ethnic/racial analyses showed that this was the case for nHw and AA patients. Hispanic and Asian patients had the highest relative survival in the earlier time period, but smaller improvement in survival was seen in these compared to other groups (see table). Age at diagnosis varied significantly between racial and ethnic groups. Age adjusted 5-year relative survival rates showed an increase of 11.7 percentage units for nHw and smaller improvements for AA, Hispanic and Asian patients (see table.) ConclusionsAlthough survival improved greatly for nHw with myeloma between 1993–97 and 2003–07, smaller improvements were observed for people of other racial or ethnic groups. Possible reasons for this disparity include lower rates of transplant among patients of minority ethnic or racial background, less frequent use of newer treatment options, later diagnosis, and differences in response rates to newer medications. Further explanatory studies are required to investigate these possibilities.Table:Five year relative survival rates by ethnic group for all age groups.a. Unadjusted estimates5-year relative survival rates (SE)Diffp-valueMedian age*1993-972003-07all30.4 (0.6)38.8 (0.6)+8.4<0.000169nHw29.2 (0.7)38.5 (0.7)+9.4<0.000170AA32.9 (1.5)38.7 (1.5)+5.80.0164Hispanic36.1 (3.1)39.1 (2.6)+30.565Asian40.9 (4.8)44.6 (4)+3.70.673*Median age at diagnosis in 2003–07b. Age-adjusted estimates5-year relative survival rates (SE)Diffp-value1993-972003-07all31.3 (0.7)41.1 (0.7)+9.8<0.0001nHw30.5 (0.8)42.2 (0.8)+11.7<0.0001AA32.3 (1.7)36.9 (1.7)+4.60.03Hispanic34.5 (3.6)38.9 (2.9)+4.40.8Asian40.6 (5.4)46.1 (4.1)+5.50.4SE=standard errorDiff=difference between 1993–97 and 2003–07 periodsp-value comparing 1993–97 and 2003–07 Disclosures:No relevant conflicts of interest to declare.

Model‐based projections for deriving up‐to‐date cancer survival estimates: An international evaluation

Model-based projections were shown to be useful for deriving most up-to-date population-based cancer survival estimates. However, the performance of these projections, which can be derived by various approaches, has only been evaluated in very few cancer patient populations. Using incidence and follow-up data for 22 common cancers from 9 long-standing population-based cancer registries from diverse parts of Europe, we compared the performance of model-based period and cohort analysis for predicting 5-year relative survival of patients diagnosed in 1996-2000 against standard survival analysis approaches (cohort, complete and period analysis). Overall, model-based predictions provided a best estimate of the later observed actual survival in 135 of 198 occasions, compared to 25, 18 and 33 occasions for cohort, complete and period analysis, respectively. Projections based on cohort and period type modeling performed essentially equally well on average, and their performance was better for more common cancers, in registries with larger population bases, and for cancers subjected to continuous clinical progress and/or ongoing screening efforts. Projections from model-based analysis may contribute to improved timeliness of monitoring of concurrent trends in population-based cancer survival in cancer registries operating in different populations and socioeconomic environments.

Trends in cancer survival in 11 European populations from 1990 to 2009: a model-based analysis

BackgroundThe timely provision and interpretation of trends in population-based cancer survival estimates is an important clinical and public health priority. Materials and methodsWe examined survival trends between 1990–1994 and 2000–2004 for 15 common cancers in 10 countries from diverse areas of Europe and provide projected survival estimates for 2005–2009, using novel techniques of model-based period analysis. ResultsBetween 1990–1994 and 2000–2004, the 5-year relative survival increased significantly in all participating registries among patients with prostate, breast, and colorectal cancers and in at least 7 of 11 registries for stomach, corpus uteri, ovarian, kidney, and thyroid cancers, as well as for non-Hodgkin’s lymphoma. Projections suggest further substantial increases in survival in the calendar period 2005–2009. For most cancer sites amenable to effective early detection and treatment, major geographical differences persist with lower survival in Eastern European countries. ConclusionsModel-based period analysis may be useful in providing population-based cancer survival estimates for currently diagnosed cancer patients. Concerted efforts in the organisation and quality control of cancer care will be very important to achieving further improvements in cancer control in Europe, and improving outcomes in Eastern European populations remains a priority.

15-Prostaglandin Dehydrogenase Expression Alone or in Combination with ACSM1 Defines a Subgroup of the Apocrine Molecular Subtype of Breast Carcinoma

Established histopathological criteria divide invasive breast carcinomas into defined groups. Ductal of no specific type and lobular are the two major subtypes accounting for around 75 and 15% of all cases, respectively. The remaining 10% include rarer types such as tubular, cribriform, mucinous, papillary, medullary, metaplastic, and apocrine breast carcinomas. Molecular profiling technologies, on the other hand, subdivide breast tumors into five subtypes, basal-like, luminal A, luminal B, normal breast tissue-like, and ERBB2-positive, that have different prognostic characteristics. An additional subclass termed "molecular apocrine" has recently been described, but these lesions did not exhibit all the histopathological features of classical invasive apocrine carcinomas (IACs). IACs make up 0.5-3% of the invasive ductal carcinomas, and despite the fact that they are morphologically distinct from other breast lesions, there are presently no standard molecular criteria available for their diagnosis and as a result no precise information as to their prognosis. Toward this goal our laboratories have embarked in a systematic proteomics endeavor aimed at identifying biomarkers that may characterize and subtype these lesions as well as targets that may lead to the development of novel targeted therapies and chemoprevention strategies. By comparing the protein expression profiles of apocrine macrocysts and non-malignant breast epithelial tissue we have previously reported the identification of a few proteins that are specifically expressed by benign apocrine lesions as well as by the few IACs that were available to us at the time. Here we reiterate our strategy to reveal apocrine cell markers and present novel data, based on the analysis of a considerably larger number of samples, establishing that IACs correspond to a distinct molecular subtype of breast carcinomas characterized by the expression of 15-prostaglandin dehydrogenase alone or in combination with a novel form of acyl-CoA synthetase medium-chain family member 1 (ACSM1). Moreover we show that 15-prostaglandin dehydrogenase is not expressed by other breast cancer types as determined by gel-based proteomics and immunohistochemistry analysis and that antibodies against this protein can identify IACs in an unbiased manner in a large breast cancer tissue microarray making them potentially useful as a diagnostic aid.

Recent trends in cancer survival across Europe between 2000 and 2004: A model-based period analysis from 12 cancer registries

Background Monitoring population-based cancer survival is an essential component in the evaluation of cancer control, but subject to an inherent delay in the reporting of the most recent survival estimates with traditional techniques of analysis. Methods We examined survival trends between the years 2000 and 2004 for 20 common cancers based on follow-up data from 12 cancer registries from diverse areas of Europe using model-based period analysis techniques. Results Between 2000 and 2004, marked rises were seen in 5-year relative survival amongst patients with prostate, breast and colorectal cancer, which were statistically significant in 10, 8 and 7 of the 12 participating cancer registries, respectively. For cancer sites amenable to effective early detection and treatment, major geographical differences in patient prognosis still persisted, with a lower survival generally observed in Eastern European countries. Conclusion Model-based period analysis enables the timely monitoring of recent trends in population-based cancer survival. For colorectal and breast cancers, the identified rises in survival are probably (at least partly) explained by the improvements in clinical care and the management of the disease. Nevertheless, persisting geographic differences do point to the potential for a further reduction in the burden of cancer throughout Europe, towards which improvements in diverse areas of care, including secondary prevention, access to advances in treatment as well as subspecialisation and regionalisation of oncologic care may all contribute.

Major Improvements in Survival in Hematologic Malignancies in the Early 2000s.

Background: Recent advances in the treatment of hematologic malignancies have led to improvements in response and survival in clinical trials for several conditions. Translation of these improvements to better survival on the population level should be monitored in as timely as possible a manner.Methods: We estimated trends in relative survival in patients with common hematologic malignancies in the United States between the years 2000 and 2004 using data from the Surveillance, Epidemiology, and End Results (SEER) program, employing the recently introduced technique of modeled period analysis to provide the most up-to-date and precise estimates of survival1. We calculated survival according to gender and age group as well as overall survival for each malignancy.Results: Major improvements in 5-year relative survivals were observed for nodal and extra-nodal non-Hodgkin lymphoma (NHL) (+8.3 and +7.1 percentage points, respectively, p<0.0001), acute myeloblastic leukemia (AML) (+4.8 percentage points, p=0.005), and chronic myelocytic leukemia (CML) (+15.9 percentage points, p<0.0001). Improvement in 10-year survivals were observed in nodal and extra-nodal (EN) NHL (+8.7 and +7.8 percentage points, p<0.0001), AML (+4.3 percentage points, p=0.009), CML (+16.2 percentage points, p<0.0001), and myeloma (+3.4 percentage points, p=0.01). Statistically significant improvements in 10-year survival were seen in both genders for NHL and CML, but were limited to women for MM and AML, although a trend towards improved survival was seen in men with these conditions as well. Improvements in prognosis were largely restricted to patients aged less than 65, except for NHL and CML. Patients over 65 with EN NHL actually had a greater improvement than younger patients, with increases of 6.0 and 8.5 percentage points, respectively for patients over and under 65. The single greatest improvement observed was in patients less than 65 with CML, who had a 25.2 percentage point improvement in 10-year relative survival between 2000 and 2004.Conclusions: Application of modeled period analysis to an examination of hematologic malignancies revealed profound improvements in survival in the 5 years between 2000 and 2004. Survival in CML has improved dramatically, and major improvements were also seen for survival in NHL, AML, and MM. A combination of new therapeutic options, improved supportive care, and wider application of recent advances is likely to be responsible for the improvements observed. Our results emphasize the importance of timely information about translation of therapeutic advances into clinical practice, such as can be provided by modeled period analysis. 1. Brenner H, Hakulinen T. Up-to-date and precise estimates of cancer patient survival: model-based period analysis. Am J Epidemiol. 2006; 164:689–696.10-year survival in hematologic malignanices in 2000 and 2004MalignancyNumber10-year survival (SE)-200010-yr survival (SE)-2004DifferenceP-valueHD998978.3 (1.2)81.8 (1.1)+3.50.12NHL-nodal40,12145.4 (0.9)54.1 (0.9)+8.7<0.0001NHL-EN19,44760.1 (1.4)67.9 (1.3)+7.80.00015MM17,33014.3 (0.9)17.7 (1.0)+3.40.01ALL222226.5 (2.8)33.2 (2.9)+6.70.14CLL12,88154.2 (2.0)56.6 (2.0)+2.40.45AML10,15315.0 (1.0)19.3 (1.2)+4.30.0085CML530822.4 (2.0)38.6 (2.4)+16.2<0.0001

Maximizing the Benefits of Model-Based Period Analysis of Cancer Patient Survival

Period analysis has been shown to provide more up-to-date estimates of cancer survival than traditional methods of survival analysis. There is, however, a tradeoff between up-to-dateness and precision of period survival estimates: increasing up-to-dateness by restricting the analysis to a relatively short period, such as the most recent calendar year, goes along with loss of precision. Recently, a model-based approach was proposed, in which more precise period survival estimates for the most recent year can be obtained through modeling of survival trends within a recent 5-year period. We assess possibilities to extend the time window used for modeling to come up with even more precise, but equally accurate and up-to-date estimates of prognosis. Empirical evaluation using data from the Finnish Cancer Registry shows that extension of the time window to about 10 years provides, in most cases, as accurate results as using a 5-year time window (whereas further extension may lead to considerably less accurate results in some cases). Using 10-year time windows for modeling, SEs of survival estimates can be approximately halved compared with conventional period survival estimates for the most recent calendar year. Furthermore, we present a modification of the modeling approach, which allows extension to 10-year time windows to be achieved without the need to include additional cohorts of patients diagnosed longer time ago and which provides similarly accurate survival estimates at comparable levels of precision in most cases. Our analyses indicate opportunities to further maximize benefits of model-based period analysis of cancer survival.

Trends in population-based cancer survival in Germany: to what extent does progress reach older patients?

Background: The ageing of populations makes outcome monitoring among elderly cancer patients particularly important.Patients and methods: Using data from the population-based Cancer Registry of Saarland, we examined age-specific trends in 5-year relative survival from 1979 to 2003 for patients with 15 common cancers in Germany. Model-based period analysis was applied to estimate 5-year relative survival for four age groups (15–54, 55–64, 65–74, 75+) in the periods 1979–1983, 1984–1988, 1989–1993, 1994–1998, and 1999–2003.Results: Overall, 5-year relative survival improved steadily from 42.2% in 1979–1983 to 56.7% in 1999–2003. From the youngest to the oldest age group, 5-year relative survival increased by 14.5, 12.1, 12.5, and 8.4 percent units, respectively, after adjusting for changes in the spectrum of cancer sites, and survival significantly improved for 10, 12, 11, and 5 cancer sites, respectively. The age gradient particularly increased for cancer sites with major progress in chemotherapeutic treatment regimens, such as ovarian cancer, non-Hodgkin’s lymphoma and leukemia.Conclusions: Relative survival of cancer patients increased considerably for many forms of cancer in Germany from 1979 to 2003. Increases were much less pronounced among elderly patients, leading to an increasing age gradient in prognosis.

Up-to-Date Estimates of Cancer Patient Survival Even with Common Latency in Cancer Registration

In an era of ongoing improvement in cancer patient survival, available long-term survival figures from cancer registries are often outdated and too pessimistic for two reasons: first, delay in availability of cancer registry data, typically in the order of a few years, and, second, application of cohort-based methods of survival analysis, which provide survival estimates for patients diagnosed many years ago. We developed a model-based period analysis approach aimed to overcome both problems. We provide extensive empirical evaluation of our approach by comparing its performance with that of previously available methods for monitoring of 5- and 10-year relative survival, with the use of data from the nationwide Finnish Cancer Registry of 490,279 patients ages >/=15 years and diagnosed with one of 20 common forms of cancer between 1953 and 1997. We show that, in most cases, the model-based approach predicts 5- and 10-year relative survival expectations of newly diagnosed patients quite closely and much better than any of the previously available methods, including standard period analysis. We conclude that the model-based approach may enable deriving up-to-date cancer survival rates even with the common latency in availability of cancer registry data.

Up-to-date and Precise Estimates of Cancer Patient Survival: Model-based Period Analysis

Monitoring of progress in cancer patient survival by cancer registries should be as up-to-date as possible. Period analysis has been shown to provide more up-to-date survival estimates than do traditional methods of survival analysis. However, there is a trade-off between up-to-dateness and the precision of period estimates, in that increasing the up-to-dateness of survival estimates by restricting the analysis to a relatively short, recent time period, such as the most recent calendar year for which cancer registry data are available, goes along with a loss of precision. The authors propose a model-based approach to maximize the up-to-dateness of period estimates at minimal loss of precision. The approach is illustrated for monitoring of 5-year relative survival of patients diagnosed with one of 20 common forms of cancer in Finland between 1953 and 2002 by use of data from the nationwide Finnish Cancer Registry. It is shown that the model-based approach provides survival estimates that are as up-to-date as the most up-to-date conventional period estimates and at the same time much more precise than the latter. The modeling approach may further enhance the use of period analysis for deriving up-to-date cancer survival rates.