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Cancer survival comparisons between cohorts are often assessed by estimates of relative or net survival. These measure the difference in mortality between those diagnosed with the disease and the general population. For such comparisons methods are needed to standardize cohort structure (including age at diagnosis) and all-cause mortality rates in the general population. Standardized non-parametric relative survival measures are evaluated by determining how well they (i) ensure the correct rank ordering, (ii) allow for differences in covariate distributions, and (iii) possess robustness and maximal estimation precision. Two relative survival families that subsume the Ederer-I, Ederer-II, and Pohar-Perme statistics are assessed. The aforementioned statistics do not meet our criteria, and are not invariant under a change of covariate distribution. Existing methods for standardization of these statistics are either not invariant to changes in the general population mortality or are not robust. Standardized statistics and estimators are developed to address the deficiencies. They use a reference distribution for covariates such as age, and a reference population mortality survival distribution that is recommended to approach zero with increasing age as fast as the cohort with the worst life expectancy. Estimators are compared using a breast-cancer survival example and computer simulation. The proposals are invariant and robust, and out-perform current methods to standardize the Ederer-II and Pohar-Perme estimators in simulations, particularly for extended follow-up.

Background Appendiceal neuroendocrine tumors (aNET) are a common entity in routine medical care, with a rate per appendectomy as high as 0.3–0.9 %. Considering the relatively young age at diagnosis for these patients, exact information about the long-term prognosis of aNET is required. Survival rates vary substantially between 71 and 100 % and are mostly limited to 5 years. This investigation assessed the long-term mortality rates of patients who underwent aNET resections at fifteen hospitals. Methods Between 1990 and 2003, the 10-year survival rates of 79 patients were analyzed using risk-adjusted Cox proportional hazard regression models adjusted for population-based baseline mortality. Additionally, prognostic factors for the oncologic outcomes were assessed. Results The median follow-up of all patients was 12.1 and 13.7 years for those alive. All patients underwent curative R0 resections. No distant metastases were diagnosed. A total of 31 (39.2 %), 29 (36.7 %), 18 (22.8 %), and 1 (1.3 %) patients had stage I, IIA, IIB, and IIIB aNET, respectively, according to the latest classification by the European Neuroendocrine Tumor Society. The 10-year overall and relative survival rates were 83.6 % (95 % CI 75.5–92.6 %) and 96.7 % (95 % CI 87.5–107 %), respectively. The 10-year relative survival rate after resection of aNET did not differ from the survival of the average national population with the same age and gender ( p  = 0.947). Second primary malignancies (hazard ratio of death 7.0, 95 % CI 1.6–30.6) were identified as a significant prognosticator for long-term survival. Conclusions Long-term survival is not significantly depreciated after the curative resection of aNET.

Estimation of relative survival has become the first and the most basic step when reporting cancer survival statistics. Standard estimators are in routine use by all cancer registries. However, it has been recently noted that these estimators do not provide information on cancer mortality that is independent of the national general population mortality. Thus they are not suitable for comparison between countries. Furthermore, the commonly used interpretation of the relative survival curve is vague and misleading. The present article attempts to remedy these basic problems. The population quantities of the traditional estimators are carefully described and their interpretation discussed. We then propose a new estimator of net survival probability that enables the desired comparability between countries. The new estimator requires no modeling and is accompanied with a straightforward variance estimate. The methods are described on real as well as simulated data.

Background Using the published survival statistics from cancer registration or population‐based studies, we aimed to describe the global pattern and trend of lung cancer survival. Methods By searching SinoMed, PubMed, Web of Science, EMBASE, and SEER, all survival analyses from cancer registration or population‐based studies of lung cancer were collected by the end of November 2022. The survival rates were extracted by sex, period, and country. The observed, relative, and net survival rates of lung cancer were applied to describe the pattern and time changes from the late 1990s to the early 21st century. Results Age‐standardized 5‐year relative/net survival rate of lung cancer was typically low, with 10%–20% for most regions. The highest age‐standardized relative/net survival rate was observed in Japan (32.9%, 2010–2014), and the lowest was in India (3.7%, 2010–2014). In most countries, the five‐year age‐standardized relative/net survival rates of lung cancer were higher in females and younger people. The patients with adenocarcinoma had a better prognosis than other groups. In China, the highest 5‐year overall relative/net survival rates were 27.90% and 31.62% in men and women in Jiangyin (2012–2013). Conclusion Over the past decades, the prognosis of lung cancer has gradually improved, but significant variations were also observed globally. Worldwide, a better prognosis of lung cancer can be observed in females and younger patients. It is essential to compare and evaluate the histological or stage‐specific survival rates of lung cancer between different regions in the future. This study collected globally published data on observed and relative survival rates of lung cancer from population‐based cancer registration. Over the past decades, the prognosis of lung cancer has gradually improved. However, region, period, sex, and age might affect the survival rate of lung cancer patients. The observed and relative survival rate of lung cancer patients varies greatly among different histological types and stages.

Background Steady evolution of therapies has improved prognosis of patients with multiple myeloma (MM) over the past two decades. Yet, knowledge about survival trends and causes of death in MM might play a crucial role in long-term management of this patient collective. Here, we investigate time trends in myeloma-specific survival at the population level over two decades and analyse causes of death in times of prolonged survival. Methods Age-standardised and age group-specific relative survival (RS) of MM patients aged < 80 years at diagnosis was estimated for consecutive time periods from 2000–2019 using data from the Cancer Registry of North Rhine-Westphalia in Germany. Conditional RS was estimated for patients who already survived one to five years post diagnosis. Causes of death in MM patients were analysed and compared to the general population using standardised mortality ratios (SMR). Results Three thousand three hundred thirty-six MM cases were included in the time trend analysis. Over two decades, age-standardised 5-year RS increased from 37 to 62%. Age-specific survival improved from 41% in period 2000–2004 to 69% in period 2015–2019 in the age group 15–69 years, and from 23 to 47% in the age group 70–79 years. Conditional 5-year RS of patients who survived five years after diagnosis slightly improved as compared to unconditional 5-year RS at diagnosis. MM patients are two times more likely to die from non-myeloma malignancies (SMR = 1.97, 95% CI 1.81–2.15) and from cardiovascular diseases (SMR = 2.01, 95% CI 1.86–2.18) than the general population. Conclusions Prognosis of patients with MM has markedly improved since the year 2000 due to therapeutic advances. Nevertheless, late mortality remains a major concern. As survival improves, second primary malignancies and cardiovascular events deserve increased attention.

Background Gastric cancer poses a significant global health challenge. We aim to use period analysis to assess the changes in gastric cancer treatment at our center over the past 15 years. This study reflects the current state of gastric cancer treatment at our center and provides valuable data to support clinical advancements. Method We used period analysis to evaluate the survival status of 3915 patients with gastric cancer at Nanfang Hospital, Southern Medical University, over a 15-year period spaning from 2008 to 2022. The 5-year relative survival rates were analyzed. Result Our findings indicate that the 5-year relative survival rate at our center from 2018 to 2022 is 71.4%. From 2018 to 2022, the 5-year relative survival rates for patients aged < 40, 40–54, 55–69, and ≥ 70 reached 67.5%, 73.5%, 72.0%, and 67.1%, respectively. For stage IV patients, the 5-year relative survival rate reached 29% in 2018–2022. For stage I-III patients, the 5-year relative survival rate reached 89.7% in 2018–2022. The five-year relative survival rate for patients who underwent laparoscopic surgery at our center rose from 50.3% in 2008–2012 to 71.4% in 2018–2022. Overall, there has been a notable increase in the 5-year relative survival rates, regardless of age, gender, region, or tumor stage. Conclusion Period analysis over the past 15 years shows significant improvement in the 5-year survival rate for gastric cancer at our center. This progress is due to standardized surgical techniques, perioperative management, and immunotherapy, providing robust data for evaluating the efficacy of recent treatments.

Alveolar echinococcosis (AE) is a zoonotic disease of increasing concern worldwide. Before benzimidazole drug therapy, 10-year death rates were 90% without surgical resection. In unresectable patients, long-term benzimidazole therapy is highly effective in stabilizing the disease course. We performed a retrospective study of 334 AE patients treated at the University Hospital Zurich, Zurich, Switzerland, during 1973-2022. Annual diagnoses increased over time, and more cases were detected by chance at earlier stages. Ninety patients died, mostly from causes unrelated to AE. Relative survival of AE patients compared with the population of Switzerland demonstrated a steady decrease 5 years after diagnosis. Patient age at diagnosis was the primary variable associated with overall survival. In a propensity-score matched survival analysis, early curative surgery was associated with overall improvement but not AE-specific survival. We conclude that survival of patients with AE is limited by non-AE causes and that early curative surgery does not improve AE-specific survival.

Background The relative survival field has seen a lot of development in the last decade, resulting in many different and even opposing suggestions on how to approach the analysis. Methods We carefully define and explain the differences between the various measures of survival (overall survival, crude mortality, net survival and relative survival ratio) and study their differences using colon and prostate cancer data extracted from the national population-based cancer registry of Slovenia as well as simulated data. Results The colon and prostate cancer data demonstrate clearly that when analysing population-based data, it is useful to split the overall mortality in crude probabilities of dying from cancer and from other causes. Complemented by net survival, it provides a complete picture of cancer survival in a given population. But when comparisons of different populations as defined for example by place or time are of interest, our simulated data demonstrate that net survival is the only measure to be used. Conclusions The choice of the method should be done in two steps: first, one should determine the measure of interest and second, one should choose among the methods that estimate that measure consistently.

Racial and ethnic disparities persist in cancer survival rates across the United States, despite overall improvements. This comprehensive analysis examines trends in 5-year relative survival rates from 2002–2006 to 2015–2019 for major cancer types, elucidating differences among racial/ethnic groups to guide equitable healthcare strategies. Data from the SEER Program spanning 2000–2020 were analyzed, focusing on breast, colorectal, prostate, lung, pancreatic cancers, non-Hodgkin lymphoma, acute leukemia, and multiple myeloma. Age-standardized relative survival rates were calculated to assess racial (White, Black, American Indian/Alaska Native, Asian/Pacific Islander) and ethnic (Hispanic, Non-Hispanic) disparities, utilizing period analysis for recent estimates and excluding cases identified solely through autopsy or death certificates. While significant survival improvements were observed for most cancers, notable disparities persisted. Non-Hispanic Blacks exhibited the largest gain in breast cancer survival, with an increase of 5.2% points (from 77.6 to 82.8%); however, the survival rate remained lower than that of Non-Hispanic Whites (92.1%). Colorectal cancer survival declined overall (64.7–64.1%), marked by a 6.2% point drop for Non-Hispanic American Indian/Alaska Natives (66.3–60.1%). Prostate cancer survival declined across all races, with Non-Hispanic American Indian/Alaska Natives showing a decrease of 7.7% points (from 96.9 to 89.2%). Lung cancer, acute leukemia, and multiple myeloma showed notable increases across groups. Substantial racial/ethnic disparities in cancer survival underscore the notable need for tailored strategies ensuring equitable access to advanced treatments, particularly addressing significant trends in colorectal and pancreatic cancers among specific minority groups. Careful interpretation of statistical significance is warranted given the large dataset.

Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15-80 years old diagnosed with colon cancer in 2001-2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use.