Statistical projection methods for lung cancer incidence and mortality: a systematic review

Trends in lung cancer incidence in Spain (1990-2019): insights from Global Burden of Diseases data

BACKGROUND

This study examines lung cancer incidence in Spain (1990-2019) through age-period-cohort (A-P-C) analysis and Global Burden of Diseases (GBD) data, unravelling the complex interplay of age, period, and birth cohort in shaping these trends.

METHODS

Utilizing GBD and Spanish population data, the study calculates age-standardized incidence rates (ASIRs) and employs Joinpoint analysis to identify significant trends. A-P-C analysis dissects the individual effects of age, calendar period, and birth cohort on incidence patterns.

RESULTS

Between 1990 and 2019, almost 738,000 cases of lung cancer were diagnosed in Spain, with an average annual increase of 1.7%. The ASIR of lung cancer in Spain from 1990 to 2019 showed a sustained upward trend in women (Average Annual Per cent Change: 2.5%, P < 0.05), reaching 23.3 cases per 100,000 in 2019, whilst men experienced a significant decrease in incidence rates (AAPC: -0.6%, P < 0.05), falling to 108.9 in 2019. The male-to-female incidence ratio decreased from 12.2 in 1992 to 4.9 in 2019. Joinpoint analysis identified distinct periods for both sexes, with men showing stability, decline and then a significant decrease, whereas women showed an initial increase followed by a decrease. The longitudinal age curves showed a consistently higher incidence risk in men, peaking in the 80-84 age group. Male cohorts since the 1920s showed a decreasing relative risk, whereas women showed fluctuations in risk over time.

CONCLUSION

Lung cancer rates are falling in Spain, especially amongst men, due to lower smoking rates. The gender gap is closing, but prevention targeted at women is needed. Tighter tobacco control and research into other risk factors are essential. Understanding the long-term effects of smoking and early exposure is key to better prevention and treatment in Spain.

Lung Cancer Prevalence in Virginia: A Spatial Zipcode-Level Analysis via INLA

BACKGROUND

Examining lung cancer (LC) cases in Virginia (VA) is essential due to its significant public health implications. By studying demographic, environmental, and socioeconomic variables, this paper aims to provide insights into the underlying drivers of LC prevalence in the state adjusted for spatial associations at the zipcode level.

METHODS

We model the available VA zipcode-level LC counts via (spatial) Poisson and negative binomial regression models, taking into account missing covariate data, zipcode-level spatial association and allow for overdispersion. Under latent Gaussian Markov Random Field (GMRF) assumptions, our Bayesian hierarchical model powered by Integrated Nested Laplace Approximation (INLA) considers simultaneous (spatial) imputation of all missing covariates through elegant prediction. The spatial random effect across zip codes follows a Conditional Autoregressive (CAR) prior.

RESULTS

Zip codes with elevated smoking indices demonstrated a corresponding increase in LC counts, underscoring the well-established connection between smoking and LC. Additionally, we observed a notable correlation between higher Social Deprivation Index (SDI) scores and increased LC counts, aligning with the prevalent pattern of heightened LC prevalence in regions characterized by lower income and education levels. On the demographic level, our findings indicated higher LC counts in zip codes with larger White and Black populations (with Whites having higher prevalence than Blacks), lower counts in zip codes with higher Hispanic populations (compared to non-Hispanics), and higher prevalence among women compared to men. Furthermore, zip codes with a larger population of elderly people (age ≥ 65 years) exhibited higher LC prevalence, consistent with established national patterns.

CONCLUSIONS

This comprehensive analysis contributes to our understanding of the complex interplay of demographic and socioeconomic factors influencing LC disparities in VA at the zip code level, providing valuable information for targeted public health interventions and resource allocation. Implementation code is available at GitHub.

Enhancement of cisplatin-induced apoptosis by saffron in human lung cancer cells

BACKGROUND

Cisplatin is a prevalent chemotherapeutic agent, and it has been used extensively to treat lung cancer. However, its clinical efficacy is hampered by its safety profile and dose-limiting toxicity. Saffron is a natural product that has shown significant anticancer effects. The combination treatment of saffron with chemotherapeutic agents has been considered a new strategy.

METHODS

Herein, saffron extract as a natural anticancer substance was combined with cisplatin to assess their combined efficacy against tumor development in vitro. In A549 and QU-DB cell lines, the combined effect of the saffron extract with cisplatin led to a significant reduction in cell viability as compared to cisplatin alone.

RESULTS

After 48 h incubation a considerable reduction in ROS levels in the QU-DB cell line upon treatment with cisplatin in the presence of saffron extract in comparison with cells treated with cisplatin alone. Furthermore, apoptosis increased significantly when in cells treated with cisplatin in combination with saffron extract compared to cisplatin alone.

CONCLUSION

Our data establish that the combination of saffron extract as a natural anticancer substance with cisplatin leads to improved cell toxicity of cisplatin as an anticancer agent. Therefore, the saffron extract could be potentially used as an additive to enable a reduction in cisplatin dosages and its side effects.

Long-Term Projections of Cancer Incidence and Mortality in Japan and Decomposition Analysis of Changes in Cancer Burden, 2020-2054: An Empirical Validation Approach

PURPOSE

The aim of this study was to project new cancer cases/deaths forward to 2054, and decompose changes in cancer cases/deaths to assess the impact of demographic transitions on cancer burden.

METHODS

We collected data on cancer cases/deaths up to 2019, empirically validated the projection performance of multiple statistical models, and selected optimal models by applying time series cross-validation.

RESULTS

We showed an increasing number of new cancer cases but decreasing number of cancer deaths in both genders, with a large burden attributed to population aging. We observed the increasing incidence rates in most cancer sites but reducing rates in some infection-associated cancers, including stomach and liver cancers. Colorectal and lung cancers were projected to remain as leading cancer burdens of both incidence and mortality in Japan over 2020-2054, while prostate and female breast cancers would be the leading incidence burdens among men and women, respectively.

CONCLUSIONS

Findings from decomposition analysis require more supportive interventions for reducing mortality and improving the quality of life of Japanese elders. We emphasize the important role of governments and policymakers in reforming policies for controlling cancer risk factors, including oncogenic infections. The rapid increase and continued presence of those cancer burdens associated with modifiable risk factors warrant greater efforts in cancer control programs, specifically in enhancing cancer screening and controlling cancer risk factors in Japan.

An Automatic Segmentation Method for Lung Tumor Based on Improved Region Growing Algorithm

In medical image processing, accurate segmentation of lung tumors is very important. Computer-aided accurate segmentation can effectively assist doctors in surgery planning and treatment decisions. Although the accurate segmentation results of lung tumors can provide a reliable basis for clinical treatment, the key to obtaining accurate segmentation results is how to improve the segmentation performance of the algorithm. We propose an automatic segmentation method for lung tumors based on an improved region growing algorithm, which uses the prior information on lung tumors to achieve an automatic selection of the initial seed point. The proposed method includes a seed point expansion mechanism and an automatic threshold update mechanism and takes the combination of multiple segmentation results as the final segmentation result. In the lung image database consortium (LIDC-IDRI) dataset, we designed 10 experiments to test the proposed method and compare it with 4 popular segmentation methods. The experimental results show that the average dice coefficient obtained by the proposed method is 0.936 ± 0.027, and the average Jaccard distance is 0.114 ± 0.049. The average dice coefficient obtained by the proposed method is 0.107, 0.053, 0.040, and 0.156, higher than that of the other four methods, respectively. This study proves that the proposed method can automatically segment lung tumors in CT slices and has suitable segmentation performance.

Forecasting of overall and aggressive prostate cancer incident counts at the small area level

OBJECTIVES

This study aims to forecast overall and aggressive prostate cancer counts at the local government area (LGA) level over 10 years (2019-2028) in Victoria, Australia, using Victorian Cancer Registry (2001-2018) data.

METHODS

We used the Age-Period-Cohort approach to estimate the annual age-specific incidence and used Bayesian spatiotemporal models that account for non-linear temporal trends and area-level risk factors. We evaluated the models' performance by withholding and comparing forecasts with the 2014-2018 data.

RESULTS

There were 80,449 prostate cancer cases between 2001 and 2018, with an overall increasing trend. Compared to 2001, prostate cancer incidence increased by 69%, from 3049 to 5167 cases in 2018. Prostate cancer counts are expected to reach 7631 cases in 2028, a further 48% increase. Unexplained area-level spatial variation was substantially reduced after adjusting for the area-level elderly population. Aggressive prostate cancer cases increased by 107% between 2001 and 2018 and are expected to rise by 123% increase in 2028. The proportion of aggressive prostate cancer cases will increase to 31% in 2028 from 20% in 2018. By 2028, overall and aggressive prostate cancer cases are projected to be increasing in 66% and 61% of LGAs.

CONCLUSION

Prostate cancer cases are projected to rise at the state level and most LGAs in the next 10 years, with much steeper increases in aggressive cases. Population growth and an ageing population have primarily contributed to this rise besides prostate-specific antigen testing. These prediction estimates help inform prostate cancer burden and facilitate efficient healthcare delivery.

Projections of smoking-related cancer mortality in Australia to 2044

BACKGROUND

While many high-income countries including Australia have successfully implemented a range of tobacco control policies, smoking remains the leading preventable cause of cancer death in Australia. We have projected Australian mortality rates for cancer types, which have been shown to have an established relationship with cigarette smoking and estimated numbers of cancer deaths attributable to smoking to 2044.

METHODS

Cancer types were grouped according to the proportion of cases currently caused by smoking: 8%-30% and >30%. For each group, an age-period- cohort model or generalised linear model with cigarette smoking exposure as a covariate was selected based on the model fit statistics and validation using observed data. The smoking-attributable fraction (SAF) was calculated for each smoking-related cancer using Australian smoking prevalence data and published relative risks.

RESULTS

Despite the decreasing mortality rates projected for the period 2015-2019 to 2040-2044 for both men and women, the overall number of smoking-related cancer deaths is estimated to increase by 28.7% for men and 35.8% for women: from 138 707 (77 839 men and 60 868 women) in 2015-2019 to 182 819 (100 153 men and 82 666 women) in 2040-2044. Over the period 2020-2044, there will be 254 583 cancer deaths (173 943 men and 80 640 women) directly attributable to smoking, with lung, larynx, oesophagus and oral (comprising lip, oral cavity and pharynx) cancers having the largest SAFs.

INTERPRETATION

Cigarette smoking will cause over 250 000 cancer deaths in Australia from 2020 to 2044. Continued efforts in tobacco control remain a public health priority, even in countries where smoking prevalence has substantially declined.

Cancer incidence and mortality in Australia from 2020 to 2044 and an exploratory analysis of the potential effect of treatment delays during the COVID-19 pandemic: a statistical modelling study

BACKGROUND

Long-term projections of cancer incidence and mortality estimate the future burden of cancer in a population, and can be of great use in informing the planning of health services and the management of resources. We aimed to estimate incidence and mortality rates and numbers of new cases and deaths up until 2044 for all cancers combined and for 21 individual cancer types in Australia. We also illustrate the potential effect of treatment delays due to the COVID-19 pandemic on future colorectal cancer mortality rates.

METHODS

In this statistical modelling study, cancer incidence and mortality rates in Australia from 2020 to 2044 were projected based on data up to 2017 and 2019, respectively. Cigarette smoking exposure (1945-2019), participation rates in the breast cancer screening programme (1996-2019), and prostate-specific antigen testing rates (1994-2020) were included where relevant. The baseline projection model using an age-period-cohort model or generalised linear model for each cancer type was selected based on model fit statistics and validation with pre-COVID-19 observed data. To assess the impact of treatment delays during the COVID-19 pandemic on colorectal cancer mortality, we obtained data on incidence, survival, prevalence, and cancer treatment for colorectal cancer from different authorities. The relative risks of death due to system-caused treatment delays were derived from a published systematic review. Numbers of excess colorectal cancer deaths were estimated using the relative risk of death per week of treatment delay and different durations of delay under a number of hypothetical scenarios.

FINDINGS

Projections indicate that in the absence of the COVID-19 pandemic effects, the age-standardised incidence rate for all cancers combined for males would decline over 2020-44, and for females the incidence rate would be relatively stable in Australia. The mortality rates for all cancers combined for both males and females are expected to continuously decline during 2020-44. The total number of new cases are projected to increase by 47·4% (95% uncertainty interval [UI] 35·2-61·3) for males, from 380 306 in 2015-19 to 560 744 (95% UI 514 244-613 356) in 2040-44, and by 54·4% (95% UI 40·2-70·5) for females, from 313 263 in 2015-19 to 483 527 (95% UI 439 069-534 090) in 2040-44. The number of cancer deaths are projected to increase by 36·4% (95% UI 15·3-63·9) for males, from 132 440 in 2015-19 to 180 663 (95% UI 152 719-217 126) in 2040-44, and by 36·6% (95% UI 15·8-64·1) for females, from 102 103 in 2015-19 to 139 482 (95% UI 118 186-167 527) in 2040-44, due to population ageing and growth. The example COVID-19 pandemic scenario of a 6-month health-care system disruption with 16-week treatment delays for colorectal cancer patients could result in 460 (95% UI 338-595) additional deaths and 437 (95% UI 314-570) deaths occurring earlier than expected in 2020-44.

INTERPRETATION

These projections can inform health service planning for cancer care and treatment in Australia. Despite the continuous decline in cancer mortality rates, and the decline or plateau in incidence rates, our projections suggest an overall 51% increase in the number of new cancer cases and a 36% increase in the number of cancer deaths over the 25-year projection period. This means that continued efforts to increase screening uptake and to control risk factors, including smoking exposure, obesity, physical inactivity, alcohol use, and infections, must remain public health priorities.

FUNDING

Partly funded by Cancer Council Australia.

Forecast of peak attainment and imminent decline after 2017 of oral cancer incidence in men in Taiwan

Oral cancer is the fourth most common cancer among men in Taiwan. The age-standardized incidence rate of oral cancer among men in Taiwan has increased since 1980 and became six times greater in 2014. To enable effective public health planning for oral cancer, research on the projection of oral cancer burden is essential. We conducted an age-period-cohort analysis on the incidence of oral cancer among men in Taiwan from 1997 to 2017 and extrapolated the trend to 2025. We found that the period trends for young adults aged between 25 and 44 have already peaked before 2017; the younger, the earlier, and then the trends declined. The cohort trends have peaked roughly at the 1972 birth cohort and then declined for all ages. Despite the increasing trend in the age-standardized incidence rate for oral cancer among men in Taiwan from 1997 to 2017, we forecast a peak attained, an imminent decline after 2017, and a decrease of 8.4% in age-standardized incidence rate from 2017 to 2025. The findings of this study contribute to developing efficient and comprehensive strategies for oral cancer prevention and control.

Approaches to the problem of nonidentifiability in the age-period-cohort models in the analysis of cancer mortality: a scoping review

Aiming to detect age, period and cohort effects in cancer mortality, age-period-cohort models (APC) can be applied to distinguish these effects. The main difficulty with adjusting an APC model involving age, period and cohort factors is the linear relationship between them, leading to a condition known as the 'nonidentifiability problem'. Many methods have been developed by statisticians to solve it, but there is not a consensus. All these existing methods, with their advantages and disadvantages, create confusion when choosing which one of them should be implemented. In this context, the present scoping review intends not to show all methods developed to avoid the nonidentifiability problem on APC models but to show which of them are, in fact, applied in the literature, especially in the cancer mortality studies. A search strategy was made to identify evidence on MEDLINE (PubMed), Scopus, EMBASE, Science Direct and Web of Science. A total of 46 papers were analyzed. The main methods found were: Holford's method (n = 14; 30%), ntrinsic estimator (n = 10; 22%), Osmond & Gardner method n = 8; 17%), Carstensen (n = 6;13%), Bayesian approach (n = 6;13%) and others (n = 2; 5%). Even with their limitations, all methods have beneficial applications. However, the decision to use one or another method seemed to be more related to an observed geographic pattern.

Trends in lung cancer incidence by age, sex and histology from 2012 to 2025 in Catalonia (Spain)

Lung cancer remains one the most common cancers in Europe and ranks first in terms of cancer mortality in both sexes. Incidence rates vary by region and depend above all on the prevalence of tobacco consumption. In this study we describe recent trends in lung cancer incidence by sex, age and histological type in Catalonia and project changes according to histology by 2025. Bayesian age-period-cohort models were used to predict trends in lung cancer incidence according to histological type from 2012 to 2025, using data from the population-based Catalan cancer registries. Data suggest a decrease in the absolute number of new cases in men under the age of 70 years and an increase in women aged 60 years or older. Adenocarcinoma was the most common type in both sexes, while squamous cell carcinoma and small cell carcinoma were decreasing significantly among men. In both sexes, the incident cases increased by 16% for patients over 70 years. Increases in adenocarcinoma and rising incidence in elderly patients suggest the need to prioritize strategies based on multidisciplinary teams, which should include geriatric specialists.

Exposure-lag response of smoking prevalence on lung cancer incidence using a distributed lag non-linear model

The prevalence of smokers is a major driver of lung cancer incidence in a population, though the “exposure–lag” effects are ill-defined. Here we present a multi-country ecological modelling study using a 30-year smoking prevalence history to quantify the exposure–lag response. To model the temporal dependency between smoking prevalence and lung cancer incidence, we used a distributed lag non-linear model (DLNM), controlling for gender, age group, country, outcome year, and population at risk, and presented the effects as the incidence rate ratio (IRR) and cumulative incidence rate ratio (IRR_cum). The exposure–response varied by lag period, whilst the lag–response varied according to the magnitude and direction of changes in smoking prevalence in the population. For the cumulative lag–response, increments above and below the reference level was associated with an increased and decreased IRR_cum respectively, with the magnitude of the effect varying across the lag period. Though caution should be exercised in interpretation of the IRR and IRR_cum estimates reported herein, we hope our work constitutes a preliminary step towards providing policy makers with meaningful indicators to inform national screening programme developments. To that end, we have implemented our statistical model a shiny app and provide an example of its use.

Effect of ultrasound-guided pulsed radiofrequency on intercostal neuralgia after lung cancer surgery: A retrospective study

This retrospective study investigated the effect of ultrasound-guided pulsed radiofrequency (UGPRF) on intercostal neuralgia (ICN) after lung cancer surgery (LCS).This retrospective observational study analyzed the outcome data of UGPRF on ICN in 80 patients with LCS. All those patients were allocated into a treatment group (n = 40) and a control group (n = 40). All patient data were collected between January 2018 and November 2019. The primary outcome was pain intensity (measured by numerical rating scale, NRS). The secondary outcomes were sleep quality (measured by Pittsburgh Sleep Quality Index, PSQI), anesthetic consumption, and treatment-related adverse events.After treatment, patients in the treatment group showed better outcomes in NRS (P < .01), PSQI (P < .01), and anesthetic consumption (P < .01), than patients in the control group. No treatment-related adverse events were documented in both groups in this study.The results of this study found that UGPRF may benefit patients for pain relief of ICN after LCS.

Forecasting of Lung Cancer Incident Cases at the Small-Area Level in Victoria, Australia

Predicting lung cancer cases at the small-area level is helpful to quantify the lung cancer burden for health planning purposes at the local geographic level. Using Victorian Cancer Registry (2001-2018) data, this study aims to forecast lung cancer counts at the local government area (LGA) level over the next ten years (2019-2028) in Victoria, Australia. We used the Age-Period-Cohort approach to estimate the annual age-specific incidence and utilised Bayesian spatio-temporal models that account for non-linear temporal trends and area-level risk factors. Compared to 2001, lung cancer incidence increased by 28.82% from 1353 to 1743 cases for men and 78.79% from 759 to 1357 cases for women in 2018. Lung cancer counts are expected to reach 2515 cases for men and 1909 cases for women in 2028, with a corresponding 44% and 41% increase. The majority of LGAs are projected to have an increasing trend for both men and women by 2028. Unexplained area-level spatial variation substantially reduced after adjusting for the elderly population in the model. Male and female lung cancer cases are projected to rise at the state level and in each LGA in the next ten years. Population growth and an ageing population largely contributed to this rise.

Projections of the future burden of cancer in Australia using Bayesian age-period-cohort models

BACKGROUND

Accurate forecasts of cancer incidence, with appropriate estimates of uncertainty, are crucial for planners and policy makers to ensure resource availability and prioritize interventions. We used Bayesian age-period-cohort (APC) models to project the future incidence of cancer in Australia.

METHODS

Bayesian APC models were fitted to counts of cancer diagnoses in Australia from 1982 to 2016 and projected to 2031 for seven key cancer types: breast, colorectal, liver, lung, non-Hodgkin lymphoma, melanoma and stomach. Aggregate cancer data from population-based cancer registries were sourced from the Australian Institute of Health and Welfare.

RESULTS

Over the projection period, total counts for these cancer types increased on average by 3 % annually to 100 385 diagnoses in 2031, which is a 50 % increase over 2016 numbers, although there is considerable uncertainty in this estimate. Counts for each cancer type and sex increased over the projection period, whereas decreases in the age-standardized incidence rates (ASRs) were projected for stomach, colorectal and male lung cancers. Large increases in ASRs were projected for liver and female lung cancer. Increases in the percentage of colorectal cancer diagnoses among younger age groups were projected. Retrospective one-step-ahead projections indicated both the incidence and its uncertainty were successfully forecast.

CONCLUSIONS

Increases in the projected incidence counts of key cancer types are in part attributable to the increasing and ageing population. The projected increases in ASRs for some cancer types should increase motivation to reduce sedentary behaviour, poor diet, overweight and undermanagement of infections. The Bayesian paradigm provides useful measures of the uncertainty associated with these projections.

The Beginning of the Trend Change in Lung Cancer Mortality Trends in Spain, 1980-2018

BACKGROUND

Recently, some countries have shown stable trends in lung cancer death rates among women not yet described for Spain. We propose to update lung cancer mortality rates in Spain during the period of 1980-2018 by sex and region.

METHODS

We used lung cancer mortality (International Classification of Diseases code 162 for the 9th edition, and codes C33 and C34 for 10th edition) and population data from the Spanish National Statistics Institute for the period 1980-2018. Age-standardised mortality rates (ASMRs), all ages and 30-64 years, by region and sex were assessed through joinpoint regression.

RESULTS

During the study period lung cancer ASMRs (all ages) in men decreased -0.4% per annum and increased by 3.1% in women. Recently, ASMR (30-64 years) accelerated its decrease (1992-2007; -0.7 and 2007-2018; -3.5%) in men and slowed its increase (1990-2012; 5.7% and 2012-2018; 1.4%) in women. In men, joinpoint analysis detected an initial period in all Autonomous Communities (ACs) in which the rates significantly increased, followed by a second period in which the rates decreased significantly (12 ACs) or remained stable (4 ACs) since the late 1980s or early 1990s. In women, upward trends in ASMRs (all ages) were observed for the whole period in all the ACs. In 13 ACs, an initial period was detected with joinpoint in which the rates remained stable or significantly decreased, followed by a second period in which the rates increased significantly since the late 1980s or early 1990s.

CONCLUSIONS

Our study shows gender differences in lung cancer mortality trends in Spain. These differences may be explained by the increased use of tobacco among women and the decreased use among men.

How Well Have Projected Lung Cancer Rates Predicted the Actual Observed Rates?

Background:

While many past studies have constructed projections of future lung cancer rates, little is known about their consistency with the corresponding observed data for the time period covered by the projections. The aim of this study was to assess the agreement between previously published lung cancer incidence and/or mortality rate projections and observed rates.

Methods:

Published studies were included in the current study if they projected future lung cancer rates for at least 10 years beyond the period for which rates were used to obtain the projections, and if more recent observed rates for comparison covered a minimum of 10 years from the beginning of the projection period. Projected lung cancer incidence and/or mortality rates from these included studies were extracted from the publications. Observed rates were obtained from cancer registries or the World Health Organization’s Mortality Database. Agreement between projected and observed rates was assessed and the relative difference (RD) for each projected rate was calculated as the percentage difference between the projected and observed rates.

Results:

A total of 59 projections reported in 14 studies were included. Nine studies provided projections for 20 years or more. RDs were higher for those projections in which the lung cancer rates peaked during the projection period, and RDs increased substantially with the length of the projection period. When lung cancer rates peaked during the projection period, methods incorporating smoking data were generally more successful at predicting the trend reversal than those which did not incorporate smoking data. Mean RDs for 15-year projections comparing methods with or without smoking data were 12.7% versus 48.0% for males and 8.2% versus 42.3% for females.

Conclusions:

The agreement between projected and observed lung cancer rates is dependent on the trends in the observed rates and characteristics of the population, particularly trends in smoking.

Impact of Tobacco Control Policies on Smoking-Related Cancer Incidence in Germany 2020 to 2050-A Simulation Study

BACKGROUND

Germany is known for its weak tobacco control. We aimed to provide projections of potentially avoidable cancer cases under different tobacco control policy intervention scenarios.

METHODS

To estimate numbers and proportions of potentially avoidable cancer cases under different policy intervention scenarios (cigarette price increases, comprehensive marketing ban, and plain packaging), we calculated cancer site-specific potential impact fractions by age, sex, and year of study period (2020-2050), considering latency periods between reduction in smoking prevalence and manifestation in declining cancer excess risks. To obtain estimates of future incident case numbers, we assumed a continuation of recent smoking trends, and combined German cancer registry data with forecasted population sizes, published effect sizes, and national daily smoking prevalence data.

RESULTS

Over a 30-year horizon, an estimated 13.3% (men 14.0% and women 12.2%) of smoking-related cancer cases could be prevented if a combination of different tobacco control policies were to be implemented in Germany, with repeated price increases being the most effective single policy (men 8.5% and women 7.3%). Extensive sensitivity analyses indicated that the model is fairly robust.

CONCLUSIONS

Our results suggest that the expected cancer incidence in Germany could be considerably reduced by implementing tobacco control policies as part of a primary cancer prevention strategy.

IMPACT

Our straightforward modeling framework enables a comparison of the impact of different health policy measures. To further accelerate the currently observed tentative trend of declining smoking prevalence in Germany and thereby curtail smoking-related cancer incidence, there is a great need to urgently intensify efforts in tobacco control.

A modified Prevalence Incidence Analysis Model method may improve disease prevalence prediction

OBJECTIVES

The Prevalence Incidence Analysis Model method is used for predicting disease prevalence, using past data on incidence and relative survival. Our objective was to propose and evaluate a modified approach for choosing the Prevalence Incidence Analysis Model.

STUDY DESIGN AND SETTING

Instead of the standard approach using the likelihood ratio statistic, we find the model that predicts most successfully the prevalence in the last available Y years using data up to but not including those Y years and then use that model to predict future prevalence another Y years ahead using all the data. We also make an "alignment" adjustment using the last known prevalence level. We evaluate the relative performance of the modified and standard methods using data on cancer from Israel in 1983-2013.

RESULTS

In this example, the modified approach gave as good or better predictions than the standard. Using the modified approach, we forecast cancer prevalence in Israel for 2014-2024 to increase at a gradually accelerating rate from the current 10,000 per year to 12,000 per year by 2020, reaching a total of 380,000 by 2024.

CONCLUSION

The modified approach may offer improved forecasting, but further methodological work on forecasting cancer prevalence is needed.