Long-term survival of cancer patients in Germany achieved by the beginning of the third millenium.

BACKGROUND: Over the last decades, long-term survival rates have substantially increased for many forms of cancer. However, these improvements have often been detected with substantial delay by traditional methods of survival analyses. PATIENTS AND METHODS: Using data of the population-based Saarland Cancer Registry, 5- and 10-year relative survival rates were derived for patients with 24 common forms of cancer in Saarland/Germany for the years 2000-2002 by period analysis and compared with conventional cohort estimates of 5- and 10-year relative survival rates pertaining to patients diagnosed in 1990-1992. RESULTS: For many forms of cancer, the 2000-2002 period survival estimates were substantially higher than the corresponding estimates for the cohorts of patients diagnosed in 1990-1992. For example, 10-year relative survival rates achieved in 2000-2002 were close to 100% for patients with testis and thyroid cancer, >85% for patients with melanomas of the skin, approximately 80% for patients with endometrial cancer and prostate cancer, close to 70% for patients with breast cancer and kidney cancer, and close to 60% for patients with colon cancer and lymphomas. CONCLUSIONS: Survival expectations of patients diagnosed with cancer at the beginning of the third millenium are substantially higher than previously available survival statistics have suggested.     

Up-to-date long-term survival curves of patients with cancer by period analysis.

PURPOSE: Provision of up-to-date long-term survival curves is an important task of cancer registries. Traditionally, survival curves have been derived for cohorts of patients diagnosed many years ago. Using data of the Finnish Cancer Registry, we provide an empirical assessment of the use of a new method of survival analysis, denoted period analysis, for deriving more up-to-date survival curves. PATIENTS AND METHODS: We calculated 10-year relative survival curves actually observed for patients diagnosed with one of the 15 most common forms of cancer in 1983 to 1987, and we compared them with the most up-to-date 10-year relative survival curves that might have been obtained in 1983 to 1987 using either traditional (cohort-wise) or period analysis. We also give the most recent 10-year survival curves obtained by period analysis for the 1993 to 1997 period. RESULTS: For all forms of cancer, period analysis of the 1983 to 1987 data yielded survival curves that were very close to the survival curves later observed for patients who were newly diagnosed in that period (median and maximum difference of 10-year relative survival estimates: 0.9 and 5.7 percent units, respectively). By contrast, the survival curves obtained by traditional (cohort-wise) survival analysis in 1983 to 1987 would have been much lower for most forms of cancer (median and maximum difference: 5.8 and 18.4 percent units, respectively). The 10-year survival curves for the 1993 to 1997 period are substantially more favorable than previously available, traditionally derived survival curves for most forms of cancer. CONCLUSION: Period analysis is a useful tool for deriving up-to-date long-term survival curves of patients with cancer.     

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.     

Period versus cohort modeling of up-to-date cancer survival

Recently, 2 modeling strategies have been proposed and shown to be useful to increase precision of up-to-date cancer survival estimates and to predict cancer patient survival: modeled period analysis and modeled cohort analysis. We aimed to compare the performance of both types of modeling for providing up-to-date and precise cancer survival estimates. Data from the nationwide Finnish Cancer Registry were used to assess how well both approaches would have been able to predict 5-year relative survival of concurrently diagnosed patients if they had been applied for that purpose throughout the past decades. Analyses were carried out for 20 common forms of cancer. For each cancer, 5-year relative survival was modeled with either approach for each single calendar year from 1962 to 1997. Mean differences and mean squared differences from 5-year relative survival later observed for patients diagnosed in the 5-year period around those calendar years were calculated. Survival estimates obtained by period modeling had much lower standard errors than those obtained by cohort modeling. Furthermore, for a clear majority of cancers, period modeling on average also provided better prediction of 5-year relative survival than cohort modeling. We conclude that, although both modeling strategies have their merits and specific indications, period modeling of survival has distinct advantages for up-to-date and precise estimation of cancer survival in population-based cancer survival studies.     

Estimates of long-term survival for newly diagnosed cancer patients: a projection approach

BACKGROUND: Patients with newly diagnosed cancer may request an estimate of their prospects for long-term survival. Unfortunately, standard estimates of survival may be outdated, because they do not reflect recent advances. The authors present a projection method that incorporates trends in survival and provides more up-to-date estimates of long-term survival for newly diagnosed patients. METHODS: The projection method fits a regression model to interval relative survival and includes a parameter associated with a trend on diagnosis year. The cumulative relative survival rate (CRS) in a target year is calculated by multiplying the projected interval survival rates for that year. To investigate the predictive ability of the projection approach and to develop model-selection rules, data from the Surveillance, Epidemiology, and End Results Program and the Connecticut tumor registry were used to recreate data that were available at a particular time in the past, and those data were used to project survival for specified target years. RESULTS: The projection method was better at predicting the survival of recently diagnosed patients than current methods, especially long-term survival for patients who had disease sites with an increasing and stable trend in survival. The authors predicted that the 15-year CRS for patients who were diagnosed in 2003 will be 61% for all cancer sites combined, 57% for colorectal cancer, 82% for female breast cancer, 53% for ovarian cancer, and 97% for prostate cancer. CONCLUSIONS: Although the projection method was more speculative than other methods that are aligned more closely with current observed data, it offered the possibility of providing improved estimates of long-term survival for recently diagnosed patients. Caution should be used when applying these methods for cancer sites where there has been a dramatic uptake of screening, e.g., prostate cancer, for which the projected results may be overly optimistic.     

Assessment of long-term survival of cancer patients using cancer registry data from eastern China: Period analysis is superior to traditional methods

We aimed to provide a systematical evaluation of the performance of period analysis compared to traditional cohort and complete methods, using cancer registry data from Taizhou, eastern China. Overall, 5-year relative survival (RS) estimate was calculated using cohort analysis, complete analysis and period analysis, respectively; further analyses were stratified by sex, region, age at diagnosis and cancer sites. Deviation value (DV), defined as the deviation between the estimated 5-year RS obtained from each method and the observed actual survival, was calculated to evaluate the accuracy of each method. Overall, 5-year RS derived by period analysis were much closer to the observed actual survival (51.4%), compared to those by complete and cohort methods, with the estimates of 48.7% (DV: −2.7%), 43.2% (DV: −8.2%) and 36.3% (DV: −15.1%), respectively. Further stratifications by sex, age at diagnosis, region and cancer sites also supported period analysis provided more precise estimates, compared to complete and cohort methods. We found, for first time systematically using cancer registry data from eastern China, period analysis provided more up-to-date precise estimates of long-term survival for overall and stratifications by sex, age at diagnosis, region and cancer sites, compared to traditional cohort and complete methods. Nevertheless, further investigations using large cancer registry data across China are warranted for the widespread use of period analysis in China.     

Cancer survival in Tianjin, China, 1991-1999

The Tianjin cancer registry was established in 1978, and registration of cases is done by the active method. The registry contributed data on 51 cancer sites or types registered during 1991-1999 for this survival study. Follow-up has been a mixture of both active and passive methods, with median follow-up ranging from 5-77 months. The proportion with histologically verified diagnosis for various cancers ranged from 21-95% and 97-100% of total registered cases were included for survival analysis. The top-ranking cancers by 5-year age-standardized relative survival (%) were renal pelvis (101%), lip (99%), corpus uteri (91%), penis and nonmelanoma skin (90%) and thyroid (89%). The corresponding survival for common cancers were lung (31%), stomach (41%), Liver (25%) and breast (82%). The 5-year relative survival by age group reveals an inverse relationship for a few cancers and fluctuated for most cancers. Period survival closely predicted the survival experience of cancer cases diagnosed in that period, with the 5-year relative survival in 1991-1995 by period approach being more or less similar to survival by cohort approach in 1996-1999 for most cancers.     

Expected long-term survival of patients diagnosed with acute myeloblastic leukemia during 2006–2010

BackgroundTreatment of acute myeloblastic leukemia (AML) has evolved over the past several decades. Therefore, currently available estimates of long-term survival, which are based on survival for patients treated with potentially now obsolete protocols, may not pertain to patients currently diagnosed.MethodsUsing data from the 1973–2005 database of the Surveillance, Epidemiology, and End Results Program, we empirically validated a novel model-based method to project 5- and 10-year relative survival of AML patients and we applied the method to project relative survival of AML patients in the United States diagnosed during 2006–2010.ResultsEmpirical evaluation indicated that the modeling approach provides more accurate estimates of currently diagnosed patients than standard methods of survival analysis, such as cohort analysis or period analysis, in the majority of cases. Projected figures for 2006–2010 show 5- and 10-year relative survival estimates of 21.4% and 18.7% for all ages combined, 62.2% and 57.4% for ages 25–34, and 60.6% and 58.1% for ages 35–44. These estimates are substantially higher than the most up-to-date estimates obtained by standard survival analysis.ConclusionPatients diagnosed with AML during 2006–2010 at younger ages have much higher long-term survival expectations than indicated by previously available survival statistics.     

Timely disclosure of progress in childhood cancer survival by 'period' analysis in the Automated Childhood Cancer Information System.

BACKGROUND: A few years ago, a new method of survival analysis, denoted 'period' analysis, was introduced to provide more up-to-date survival estimates of cancer patients. PATIENTS AND METHODS: We evaluated the period survival method using the large database of the Automated Childhood Cancer Information System (ACCIS). Our evaluation is based on data from 35 191 children diagnosed with cancer in 13 European countries between 1975 and 1989 and followed for vital status until around 1999. RESULTS: Using the follow-up data available in 1989, 10-year survival for all children with cancer calculated by the period method for the 1985-89 period was 58%, while it was 43% when calculated by traditional 'cohort' life-table analysis (based on children diagnosed in 1975-79). The period method provided a better estimate of the true 10-year survival of 62%, observed 10 years later in the cohort of patients diagnosed in 1985-89. Similar results were observed for each of the common groups of childhood cancer. CONCLUSION: Period analysis is especially useful for monitoring childhood cancer survival, because at a given point in time it provides more timely estimates of long-term survival expectations than the cohort life-table method. Using the ACCIS database, up-to-date estimates of period survival for childhood cancer are derived in subsequent papers in this journal.     

Are patients diagnosed with breast cancer before age 50 years ever cured?

PURPOSE: Breast cancer diagnosed before the age of 50 years has become a common disease in many developed countries. Although average remaining life expectancy in the affected age groups is usually several decades, data regarding survival perspectives beyond 10 to 20 years after diagnosis are sparse. The aim of this study was to assess long-term survival in a large population-based sample of patients diagnosed with breast cancer before age 50 years. PATIENTS AND METHODS: Relative survival within up to 40 years after diagnosis was assessed for cohorts of women diagnosed with breast cancer before age 50 years and notified to the nationwide Finnish Cancer Registry within various time intervals since 1953. In addition, up-to-date estimates of 40-year relative survival were obtained by exclusively looking at the survival experience of breast cancer patients in recent years (1993 to 1999) using period analysis, a new method of survival analysis. RESULTS: Prognosis of patients diagnosed with breast cancer before age 50 years has considerably improved during the past decades. According to the latest estimates from period analysis, cumulative 40-year relative survival is now approximately 43% for all cancers combined, 57% for localized cancers, and 24% for cancers with regional tumor spread. Nevertheless, patients diagnosed with breast cancer before age 50 years continue to have increased mortality throughout at least four decades after diagnosis. This applies even if breast cancer is diagnosed in a localized stage and in the absence of a second primary breast cancer. CONCLUSION: Despite major improvement in prognosis over time, breast cancer occurring among patients who are younger than 50 years remains a chronic disease that affects prognosis for decades.     

Further enhanced monitoring of cancer patient survival by stage-adjusted period analysis.

Monitoring progress in cancer patient survival is an important task of population-based cancer registration. Period analysis has been shown to provide more up-to-date estimates of cancer patient survival than traditional methods of survival analysis. However, even period estimates may disclose recent improvements in long-term survival with some delay as they are still partly based on the survival experience of patients diagnosed years ago. If these patients had a less favorable stage distribution than the patients diagnosed in a more recent calendar period (e.g., due to progress in early detection), period estimates may underestimate long-term survival for patients diagnosed in that period. This particular source of potential underestimation can be overcome by adjustment of the stage distribution of all patients included in period analysis to the stage distribution of the patients diagnosed in the period of interest. The principle, application, and use of stage adjustment of period survival estimates are illustrated with 5- and 10-year relative survival estimates of patients diagnosed with breast cancer and followed with respect to survival in the United States between 1973 and 2001, using data of the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute. We show that stage adjustment may often further enhance the benefits of period analysis for deriving up-to-date cancer survival estimates.     

Up-to-date survival curves of children with cancer by period analysis

Survival rates of children with cancer have strongly improved during the past decades, but much of this improvement has been disclosed with substantial delay by traditional methods of survival analysis, which reflect survival experience of patients diagnosed many years ago. In this paper, the use of a new method of survival analysis, denoted period analysis, for providing more up-to-date estimates of 10-year survival curves of children with cancer is empirically evaluated using data of the Surveillance, Epidemiology, and End Results Program of the United States National Cancer Institute. It is shown that period analysis provides much more up-to-date estimates of survival curves than traditional cohort-based survival analysis indeed, at least as long as there is ongoing improvement in survival rates over time, as it seems to be the case for many forms of childhood cancer. The most recent 10-year period survival estimates indicate that survival rates of children with cancer achieved by the end of the 20th century are substantially higher than previously available survival statistics have suggested. Application of period analysis may be particularly useful in the field of childhood cancer as it may help to prevent patients, their families and clinicians from being burdened by outdated, often too pessimistic survival expectations.     

Cancer survival in Qidong, China, 1992-2000

The Qidong cancer registry was established in 1972, and registration of cases is done by active and passive methods. The registry contributed data on 33 cancer sites or types registered during 1992-2000 for this survival study. Data on 22 cancers registered during 1972-2000 were utilized to elicit the survival trend by period and cohort approaches. Follow-up was done by a mixture of active and passive methods, with median follow-up ranging from 2-25 months. The proportion of cases with histologically verified cancer diagnosis ranged from 9-100%, and 87-100% of total registered cases were included for survival analysis. The top-ranking cancers on 5-year age-standardized relative survival (%) were thyroid (78%), breast (58%), corpus uteri (54%), larynx (51%) and urinary bladder (42%). The corresponding survival rates for common cancers were liver (6%), lung (7%) and stomach (18%). The 5-year relative survival by age group fluctuated and showed no distinct pattern or trend. The comparison of 5-year relative survival trend by cohort and period approaches revealed that period survival closely predicted the survival experience of cancer cases diagnosed in that period for most cancers.     

Survival and distribution pattern of childhood liver cancer in Taiwan

Studies of survival and distribution of liver cancer in children are scarce. In this study, using data from the cancer registry of Taiwan, from 1979 to 1992, we identified 377 young patients (0-15 years of age) suffering from liver cancer, coded 155 according to the International Classification of Diseases. Among these patients, 122 were histopathologically proven hepatocellular carcinoma (HCC) and 43 hepatoblastoma (HB). For survival analysis, we also searched for cases of liver cancer in 0-16 year old children in the Taiwan cancer registry for the period between 1988 and 1992. We found 109 cases with identification numbers and birth dates which allowed our cases to be linked with the death registry of the National Health Department of Taiwan enabling the calculation of 5-year survival rates using actuarial life tables. Between 1979 and 1992, for 122 HCC cases, there was a peak incidence at the age of 1 year, then a decline to a trough at the age of 4 years, after which the number of cases increased to the age of 15 years. After the age of 4 years boys outnumbered the girls by 2:1. 36 (84%) of 43 HB cases were under the age of 5 years and boys tended to outnumber girls by 2.9:1. Between 1988 and 1992, of the 109 patients, 49 were diagnosed histopathologically and 60 patients clinically. Their overall 5-year survival rate was 19%. The 5-year survival rate of the 28 HCC patients was 17%, whereas that of the 17 HB patients was 47%. In conclusion, our epidemiological findings indicate that the HCC distribution among children is different according to age and to some extent sex. The overall 5-year survival rate of children suffering from liver cancer was still unfavourable.     

Survival from colorectal cancer in Germany in the early 21st century

Background:

Colorectal cancer is the most common cancer in Germany and the second most common cause of cancer-related deaths in both men and women. The aim of this study is to provide detailed analysis of recent developments in survival of colorectal cancer patients using newly available data on a national basis.

Methods:

We included data from 11 German cancer registries covering a population of 33 million inhabitants. Period analysis and modelled period analysis were used to provide most up-to-date estimates of 5-year relative survival in 2002–2006.

Results:

The analysis was based on records of 164 996 colorectal cancer patients. Five-year relative survival was 63.0% overall, decreased with age and was significantly higher among women than among men in patients under 75 years. Overall age-adjusted 5-year relative survival increased from 60.6 to 65.0% over the period 2002–2006. Significant increase in survival was only observed in patients with localised or regional disease. Highest subsite-specific survival was observed in patients with cancer in descending (67.7%) and ascending (66.5%) colon.

Conclusion:

Survival of patients with colorectal cancer continued to increase in the early 21st century in Germany, with 5-year relative survival reaching 65% in 2006. However, lack of progress still persisted in patients with advanced disease.     

Model based hybrid analysis of cancer patient survival

In many cancer registries, registration of new cases is somewhat less up-to-date than mortality follow-up. In such situations, hybrid analysis, a combination of cohort and period analysis, rather than 'pure' period analysis has been proposed to derive up-to-date survival estimates. We evaluate application and adaptation of a modelling strategy that has recently been introduced to enhance precision of period survival estimates, to 'hybrid type of data'. Using data from the Finnish Cancer Registry, we show that modelling again strongly increases precision of survival estimates. Furthermore, special models adapted to the hybrid type of data are shown to provide even more precise and, in a clear majority of cases, also more valid predictions of survival of recently diagnosed patients than models ignoring the hybrid type of data. Finally, we show that model-based estimation of and testing for recent trends may give different answers if period rather than hybrid modelling is used for hybrid type of registry data. We conclude that modelling is useful for both hybrid and period analyses of cancer survival, but the different data structure needs to be taken into account in the set-up of models.     

Long‐term survival and conditional survival of cancer patients in Japan using population‐based cancer registry data

Although we usually report 5‐year cancer survival using population‐based cancer registry data, nowadays many cancer patients survive longer and need to be followed‐up for more than 5 years. Long‐term cancer survival figures are scarce in Japan. Here we report 10‐year cancer survival and conditional survival using an established statistical approach. We received data on 1 387 489 cancer cases from six prefectural population‐based cancer registries in Japan, diagnosed between 1993 and 2009 and followed‐up for at least 5 years. We estimated the 10‐year relative survival of patients who were followed‐up between 2002 and 2006 using period analysis. Using this 10‐year survival, we also calculated the conditional 5‐year survival for cancer survivors who lived for some years after diagnosis. We reported 10‐year survival and conditional survival of 23 types of cancer for 15–99‐year‐old patients and four types of cancer for children (0–14 years old) and adolescent and young adults (15–29 years old) patients by sex. Variation in 10‐year cancer survival by site was wide, from 5% for pancreatic cancer to 95% for female thyroid cancer. Approximately 70–80% of children and adolescent and young adult cancer patients survived for more than 10 years. Conditional 5‐year survival for most cancer sites increased according to years, whereas those for liver cancer and multiple myeloma did not increase. We reported 10‐year cancer survival and conditional survival using population‐based cancer registries in Japan. It is important for patients and clinicians to report these relevant figures using population‐based data.     

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

Abstract Purpose. Population-based studies on cervical 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 cervical cancer patients in Germany. Methods. We used a pooled German national dataset including data from 11 cancer registries covering a population of 33 million people. Included were 15 685 patients diagnosed with cervical cancer from 1997 to 2006. Period analysis was performed to calculate the five-year relative survival (RS) 2002-2006. Trends in survival between 2002 and 2006 were examined using model-based period analysis. Age-adjustment was done using five age groups (15-44, 45-54, 55-64, 65-74, and 75 + years). Results. Overall, age-adjusted five-year relative survival in 2002-2006 was 64.7%. A strong age gradient was observed, with five-year RS decreasing from 81.7% in age group 15-49 years to 46.3% in age group 70 + years. Prognosis furthermore strongly varied by stage, with age-adjusted five-year RS reaching 84.6% for localized, 48.2% for regional, and 17.9% for distant stage. From 2002 to 2006, a significant improvement (4.7 percent units) in overall age-adjusted five-year RS was seen. The improvement was most pronounced for age groups 55-64 years (from 54.2 to 65.6%) and 65-74 years (from 50.0 to 58.1%). Conclusion. In this first comprehensive population-based study from Germany, prognosis of cervical cancer strongly varied by age and stage. Prognosis continued to improve, in particular in age range 55-74 years, in the five-year period assessed.     

Recent cancer survival in Europe: a 2000-02 period analysis of EUROCARE-4 data

BACKGROUND: Traditional cancer-survival analyses provide data on cancer management at the beginning of a study period, and are often not relevant to current practice because they refer to survival of patients treated with older regimens that might no longer be used. Therefore, shortening the delay in providing survival estimates is desirable. Period analysis can estimate cancer survival by the use of recent data. We aimed to apply the period-analysis method to data that were collected by European cancer registries to estimate recent survival by country and cancer site, and to assess survival changes in Europe. We also compared our findings with data on cancer survival in the USA from the US SEER (Surveillance, Epidemiology, and End Results) programme. METHODS: We analysed survival data for patients diagnosed with cancer in 2000-02, collected from 47 of the European cancer registries participating in the EUROCARE-4 study. 5-year period relative survival for patients diagnosed in 2000-02 was estimated as the product of interval-specific relative survival values of cohorts with different lengths of follow-up. 5-year survival profiles for patients diagnosed in 2000-02 were estimated for the European mean and for five European regions, and findings were compared with US SEER registry data for patients diagnosed in 2000-02. A 5-year survival profile for patients diagnosed in 1991-2002 and a 10-year survival profile for patients diagnosed in 1997-2002 were also estimated by the period method for all malignancies, by geographical area, and by cancer site. FINDINGS: For all cancers, age-adjusted 5-year period survival improved for patients diagnosed in 2000-02, especially for patients with colorectal, breast, prostate, and thyroid cancer, Hodgkin's disease, and non-Hodgkin lymphoma. The European mean age-adjusted 5-year survival calculated by the period method for 2000-02 was high for testicular cancer (97.3% [95% CI 96.4-98.2]), melanoma (86.1% [84.3-88.0]), thyroid cancer (83.2% [80.9-85.6]), Hodgkin's disease (81.4% [78.9-84.1]), female breast cancer (79.0% [78.1-80.0]), corpus uteri (78.0% [76.2-79.9]), and prostate cancer (77.5% [76.5-78.6]); and low for stomach cancer (24.9% [23.7-26.2]), chronic myeloid leukaemia (32.2% [29.0-35.7]), acute myeloid leukaemia (14.8% [13.4-16.4]), and lung cancer (10.9% [10.5-11.4]). Survival for patients diagnosed in 2000-02 was generally highest for those in northern European countries and lowest for those in eastern European countries, although, patients in eastern European had the highest improvement in survival for major cancer sites during 1991-2002 (colorectal cancer from 30.3% [28.3-32.5] to 44.7% [42.8-46.7]; breast cancer from 60% [57.2-63.0] to 73.9% [71.7-76.2]; for prostate cancer from 39.5% [35.0-44.6] to 68.0% [64.2-72.1]). For all solid tumours, with the exception of stomach, testicular, and soft-tissue cancers, survival for patients diagnosed in 2000-02 was higher in the US SEER registries than for the European mean. For haematological malignancies, data from US SEER registries and the European mean were comparable in 2000-02, except for non-Hodgkin lymphoma. INTERPRETATION: Cancer-service infrastructure, prevention and screening programmes, access to diagnostic and treatment facilities, tumour-site-specific protocols, multidisciplinary management, application of evidence-based clinical guidelines, and recruitment to clinical trials probably account for most of the differences that we noted in outcomes.     

Cancer patient survival in Sweden at the beginning of the third millennium – predictions using period analysis

Estimates of cancer patient survival made using traditional, cohort-based, methods can be heavily influenced by the survival experience of patients diagnosed many years in the past and may not be particularly relevant to recently diagnosed patients. Period-based survival analysis has been shown to provide better predictions of survival for recently diagnosed patients and earlier detection of temporal trends in patient survival than cohort analysis. We aim to provide predictions of the long-term survival of recently diagnosed cancer patients using period analysis. The period estimates are compared with the latest available cohort-based estimates. Our results, based on period analysis for the years 2000–2002, suggest an improvement in survival for many forms of cancer during recent years. For all sites combined the 5-, 10-, 15-, and 20-year relative survival ratios were 62, 53, 48, and 47 for males and 67, 62, 60, and 59, for females. These estimates were 3–14 units higher than those obtained using the latest available cohorts with the respective lengths of follow-up. The interval-specific relative survival stabilised for males at 97 after 8years of follow-up and for females at 98 after 7years for both period and cohort analyses.