Summary Background Worldwide data for cancer survival are scarce. We aimed to initiate worldwide surveillance of cancer survival by central analysis of population-based registry data, as a metric of the effectiveness of health systems, and to inform global policy on cancer control. Methods Individual tumour records were submitted by 279 population-based cancer registries in 67 countries for 25·7 million adults (age 15–99 years) and 75 000 children (age 0–14 years) diagnosed with cancer during 1995–2009 and followed up to Dec 31, 2009, or later. We looked at cancers of the stomach, colon, rectum, liver, lung, breast (women), cervix, ovary, and prostate in adults, and adult and childhood leukaemia. Standardised quality control procedures were applied; errors were corrected by the registry concerned. We estimated 5-year net survival, adjusted for background mortality in every country or region by age (single year), sex, and calendar year, and by race or ethnic origin in some countries. Estimates were age-standardised with the International Cancer Survival Standard weights. Findings 5-year survival from colon, rectal, and breast cancers has increased steadily in most developed countries. For patients diagnosed during 2005–09, survival for colon and rectal cancer reached 60% or more in 22 countries around the world; for breast cancer, 5-year survival rose to 85% or higher in 17 countries worldwide. Liver and lung cancer remain lethal in all nations: for both cancers, 5-year survival is below 20% everywhere in Europe, in the range 15–19% in North America, and as low as 7–9% in Mongolia and Thailand. Striking rises in 5-year survival from prostate cancer have occurred in many countries: survival rose by 10–20% between 1995–99 and 2005–09 in 22 countries in South America, Asia, and Europe, but survival still varies widely around the world, from less than 60% in Bulgaria and Thailand to 95% or more in Brazil, Puerto Rico, and the USA. For cervical cancer, national estimates of 5-year survival range from less than 50% to more than 70%; regional variations are much wider, and improvements between 1995–99 and 2005–09 have generally been slight. For women diagnosed with ovarian cancer in 2005–09, 5-year survival was 40% or higher only in Ecuador, the USA, and 17 countries in Asia and Europe. 5-year survival for stomach cancer in 2005–09 was high (54–58%) in Japan and South Korea, compared with less than 40% in other countries. By contrast, 5-year survival from adult leukaemia in Japan and South Korea (18–23%) is lower than in most other countries. 5-year survival from childhood acute lymphoblastic leukaemia is less than 60% in several countries, but as high as 90% in Canada and four European countries, which suggests major deficiencies in the management of a largely curable disease. Interpretation International comparison of survival trends reveals very wide differences that are likely to be attributable to differences in access to early diagnosis and optimum treatment. Continuous worldwide surveillance of cancer surv...

and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEWThe GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).FINDINGS In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCEThe results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

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Background:Although the prognosis of most patients presenting with malignant pleural mesothelioma (MPM) is poor, a small proportion survives long term. We investigated factors associated with survival in a large patient series.Methods:All patients registered with the NSW Dust Diseases Board (2002–2009) were included in an analysis of prognostic factors using Kaplan–Meier and Cox regression analysis. On the basis of these analyses, we developed a risk score (Prognostic Index (PI)).Results:We identified 910 patients: 90% male; histology (epithelioid 60% biphasic 13% sarcomatoid 17%); stage (Tx-I-II 48% III-IV 52%); and calretinin expression (91%). Treatment: chemotherapy(CT) 44%, and extrapleural-pneumonectomy (EPP) 6%. Median overall survival (OS) was 10.0 months. Longer OS was associated with: age <70 (13.5 vs 8.5 months; P<0.001); female gender (12.0 vs 9.9 months; P<0.001); epithelioid subtype (13.3 vs 6.2 months; P<0.001); ECOG status 0 (27.4 vs 9.7 months; P=0.015), calretinin expression (10.9 vs 5.5 months; P<0.001); neutrophil–lymphocyte ratio (NLR) <5 (11.9 vs 7.5 months; P<0.001); platelet count <400 (11.5 vs 7.2 months; P<0.001); and normal haemoglobin (16.4 vs 8.8 months; P<0.001). On time-dependent analysis, patients receiving pemetrexed-based chemotherapy (HR=0.83; P=0.048) or EPP (HR=0.41; P<0.001) had improved survival. Age, gender, histology, calretinin and haematological factors remained significant on multivariate analysis. In all, 24% of patients survived >20 months: 16% of these receiving EPP, and 66% CT. The PI offered improved prognostic discrimination over one of the existing prognostic models (EORTC).Conclusions:We identified calretinin expression, age, gender, histological subtype, platelet count and haemoglobin level as independent prognostic factors. Patients undergoing EPP or pemetrexed-based chemotherapy demonstrated better survival, but 84% and 34% of long survivors, respectively, did not receive radical surgery or chemotherapy.

The distribution of ovarian cancer histology varies widely worldwide. Type I epithelial, germ cell and sex cord-stromal tumours are generally associated with higher survival than type II tumours, so the proportion of these tumours may influence survival estimates for all ovarian cancers combined. The distribution of histological groups should be considered when comparing survival between countries and regions.

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Australia's malignant mesothelioma incidence rates appear to have reached maximum levels but with differences over time by age, gender and tumour location. Improvements over time in survival provide a glimpse of hope for this almost invariably fatal disease.

Relative survival and excess mortality approaches are commonly used to estimate and compare net survival from cancer. These approaches are based on the assumption that the underlying (non-cancer) mortality rate of cancer patients is the same as that of the general population. This assumption is likely to be violated particularly in the context of smoking-related cancers. The magnitude of this bias has not been estimated. The objective of this article is to estimate the bias in relative survival ratios (RSRs) and excess mortality rate ratios (EMRRs) from using total population compared to correct subpopulation specific life-tables. Analyses were conducted on 1996-2001 linked census-cancer data (including smoking status) for people with lung and bladder cancer, using sex-specific (standard practice), sex-and ethnic-specific, sex-and smoking-specific and sex-, ethnic-and smoking-specific life-tables. Five-year RSRs using sex-specific life-tables, compared to fully stratified lifetables, were underestimated by 10-25% for current smoking and Maori populations. For example, the current smoker male bladder cancer RSR was 0.700 for sex-specific life-tables, compared to 0.838 for fully stratified life-tables. Similarly, EMRRs comparing current to never smokers and Maori to non-Maori were overestimated using sex-specific life-tables only: modestly only for lung cancer, but markedly for bladder cancer. For example, the EMRR comparing current to never smokers with bladder cancer in a fully adjusted regression model was 1.475 when using sex-specific life-tables only, but reduced to 1.098 when using fully stratified life-tables. Substantial bias can occur when estimating relative cancer survival across subpopulations if non-matching life-tables are used.Relative survival and excess mortality analyses are commonly used to estimate and compare net survival (or excess mortality) among patients with cancer. Relative survival and excess mortality analyses use overall survival and the total number of deaths, respectively, and then adjust for the expected survival and number of deaths using population life-tables. Relative survival ratios (RSRs) are calculated using the ratio of observed survival among cancer patients to the expected survival in the underlying population. Excess mortality rate modelling is a mirror image of survival analyses and usually undertaken with a Poisson model using the observed minus expected number of deaths as the dependent variable. 1-3The key advantages of relative survival and excess mortality rate methods are that error due to incorrect coding of cause of death is avoided, and that one captures cancerconsequent deaths through the difference in observed and expected deaths (or survival).2 The key disadvantage, however, is that one has to assume that the population lifetables provide accurate estimates of the expected mortality rate or survival for the people developing cancer. In other words, these methods assume that those who develop cancer would have had the same risk of mortality as the general pop...