[Purpose]To analyze the cancer incidence and mortality in 2020 and trends from 2010 to 2020 in Henan Province.[Methods]Data from cancer registries in Henan Province from 2010 to 2020 were collected and evaluated.Incidence and mortality rates were calculated by urban/rural areas,sex and age,and the incidence and mortality of cancers in the whole province in 2020 were estimated based on population data released by Henan Provincial Bureau of Statistics.Age-standardized rates were calculated according to the age-standardized rate of Chinese standard population(ASIRC/ASMRC)and world standard population(ASIRW/ASMRW).Joinpoint 5.4.0 soft-ware was used to construct a regression model to analyze the changing trends of malignant tumors from 2010 to 2020,and the average annual percentage change(AAPC)and 95％confidence in-terval were calculated.[Results]In 2020,the estimated number of new cancer cases in Henan Province was 299 148,with a crude incidence rate of 259.38/105,ASIRC of 201.09/105(204.56/105 for males and 200.45/105 for females)and ASIRW of 196.46/105(203.43/105 for males and 192.22/105 for females).The ASIRC was higher in urban areas(208.10/105)than that in rural areas(197.74/105).The top five cancer types in male were lung,stomach,liver,esophagus,and colorectal cancers,while the top five in female were breast,lung,thyroid,cervical,and esophageal cancers.The estimated number of cancer deaths was 172 070,with a crude mortality rate of 149.20/105 and ASMRC of 106.52/105(137.22/105 for males and 78.04/105 for females)and ASMRW of 106.24/105(137.05/105 for males and 77.91/105 for females).The ASMRC was higher in rural areas(109.92/105)than that in urban areas(99.49/105).The top five causes of cancer death in male were lung,stomach,liver,esophagus,and colorectal cancers,and those in female were lung,esophagus,stomach,liver,and breast cancers.From 2010 to 2020,the trends of ASIRC remained stable(AAPC=0.14％,P=0.572),while the ASMRC showed a significant decreasing trend(AAPC=-1.46％,P=0.011).[Conclusion]Lung cancer,breast cancer and digestive system cancers are the main malignant tumors threatening the health of residents in Henan Province.The incidence and mor-tality of common malignant tumors show significant gender and urban-rural differences.It is neces-sary to further optimize the prevention and control of malignant tumors,formulate targeted inter-vention strategies based on population characteristics,and improve the health awareness of the whole population.

Objective:To develop a tool package that meets the routine statistical analysis requirements of population-based cancer registries in China based on R language, with the aim of improving data quality and efficiency, and promoting the nationwide scientific utilization of cancer registry data.Methods:The functional demands for statistical analysis of population-based cancer registry staff were collected through questionnaires or face-to-face interviews. Based on the concept of generic functions in R software's S3 object system, functions were developed by defining specific S3 classes for different data types, allowing the same function to perform diverse tasks depending on the class of input data. A stepwise development strategy was adopted to ensure logical coherence among functional modules, and all functions were systematically tested and validated in accordance with standard R package development guidelines.Results:Six categories of functions, including data reading, data manipulation, data processing, statistical calculation, visualization, and statistical reporting, were developed to support routine statistical analysis of population-based cancer registry data. Data reading functions support reading data formats required by the National Cancer Registry. Data manipulation functions empower conditional filtering of registry data and support regrouping, merging, or transforming the data based on registry attributes (such as urban/rural location) to accommodate different analytical needs. Data processing functions includes age grouping, International Classification of Diseases 10 th Revision (ICD-10) classification, childhood cancer classification, and population estimation. Statistical calculation functions permit the calculation of age-standardized rates, truncated rates, cumulative rates, cumulative risks, life tables, and expansion from abridged to complete life tables. Visualization functions can generate commonly used statistical charts, including population pyramids, bar charts, and line graphs. Statistical reporting functions can integrate key indicators, charts, and narrative descriptions into comprehensive cancer registry reports. Conclusion:An R package named Canregtools was developed based on the concept of S3 generic functions. This package is free of charge, open-source, and highly efficient. It can meet the diversified needs in cancer registry data analysis, visualization, and reporting through standardized data processing workflows, thereby enhancing the quality and efficiency of routine statistical analysis in population-based cancer registries in China.

Objective:To develop a tool package that meets the routine statistical analysis requirements of population-based cancer registries in China based on R language, with the aim of improving data quality and efficiency, and promoting the nationwide scientific utilization of cancer registry data.Methods:The functional demands for statistical analysis of population-based cancer registry staff were collected through questionnaires or face-to-face interviews. Based on the concept of generic functions in R software's S3 object system, functions were developed by defining specific S3 classes for different data types, allowing the same function to perform diverse tasks depending on the class of input data. A stepwise development strategy was adopted to ensure logical coherence among functional modules, and all functions were systematically tested and validated in accordance with standard R package development guidelines.Results:Six categories of functions, including data reading, data manipulation, data processing, statistical calculation, visualization, and statistical reporting, were developed to support routine statistical analysis of population-based cancer registry data. Data reading functions support reading data formats required by the National Cancer Registry. Data manipulation functions empower conditional filtering of registry data and support regrouping, merging, or transforming the data based on registry attributes (such as urban/rural location) to accommodate different analytical needs. Data processing functions includes age grouping, International Classification of Diseases 10 th Revision (ICD-10) classification, childhood cancer classification, and population estimation. Statistical calculation functions permit the calculation of age-standardized rates, truncated rates, cumulative rates, cumulative risks, life tables, and expansion from abridged to complete life tables. Visualization functions can generate commonly used statistical charts, including population pyramids, bar charts, and line graphs. Statistical reporting functions can integrate key indicators, charts, and narrative descriptions into comprehensive cancer registry reports. Conclusion:An R package named Canregtools was developed based on the concept of S3 generic functions. This package is free of charge, open-source, and highly efficient. It can meet the diversified needs in cancer registry data analysis, visualization, and reporting through standardized data processing workflows, thereby enhancing the quality and efficiency of routine statistical analysis in population-based cancer registries in China.

[Purpose]To analyze the cancer incidence and mortality in 2020 and trends from 2010 to 2020 in Henan Province.[Methods]Data from cancer registries in Henan Province from 2010 to 2020 were collected and evaluated.Incidence and mortality rates were calculated by urban/rural areas,sex and age,and the incidence and mortality of cancers in the whole province in 2020 were estimated based on population data released by Henan Provincial Bureau of Statistics.Age-standardized rates were calculated according to the age-standardized rate of Chinese standard population(ASIRC/ASMRC)and world standard population(ASIRW/ASMRW).Joinpoint 5.4.0 soft-ware was used to construct a regression model to analyze the changing trends of malignant tumors from 2010 to 2020,and the average annual percentage change(AAPC)and 95％confidence in-terval were calculated.[Results]In 2020,the estimated number of new cancer cases in Henan Province was 299 148,with a crude incidence rate of 259.38/105,ASIRC of 201.09/105(204.56/105 for males and 200.45/105 for females)and ASIRW of 196.46/105(203.43/105 for males and 192.22/105 for females).The ASIRC was higher in urban areas(208.10/105)than that in rural areas(197.74/105).The top five cancer types in male were lung,stomach,liver,esophagus,and colorectal cancers,while the top five in female were breast,lung,thyroid,cervical,and esophageal cancers.The estimated number of cancer deaths was 172 070,with a crude mortality rate of 149.20/105 and ASMRC of 106.52/105(137.22/105 for males and 78.04/105 for females)and ASMRW of 106.24/105(137.05/105 for males and 77.91/105 for females).The ASMRC was higher in rural areas(109.92/105)than that in urban areas(99.49/105).The top five causes of cancer death in male were lung,stomach,liver,esophagus,and colorectal cancers,and those in female were lung,esophagus,stomach,liver,and breast cancers.From 2010 to 2020,the trends of ASIRC remained stable(AAPC=0.14％,P=0.572),while the ASMRC showed a significant decreasing trend(AAPC=-1.46％,P=0.011).[Conclusion]Lung cancer,breast cancer and digestive system cancers are the main malignant tumors threatening the health of residents in Henan Province.The incidence and mor-tality of common malignant tumors show significant gender and urban-rural differences.It is neces-sary to further optimize the prevention and control of malignant tumors,formulate targeted inter-vention strategies based on population characteristics,and improve the health awareness of the whole population.

Objectives:To evaluate the cost-effectiveness of typical pharmaceutical smoking cessation intervention strategies in China in the context of primary cancer prevention.Methods:Markov cohort simulation models were established to simulate the burden of 12 smoking caused cancer, including lung cancer, oral cancer, nasopharyngeal cancer, laryngeal cancer, esophageal cancer, gastric cancer, pancreatic cancer, liver cancer, kidney cancer, bladder cancer, cervical cancer, and acute myeloid leukemia. Taking incremental cost effectiveness ratio (ICER) as the main indicator, the model sets one year as the cycling period for 50 periods and simulates the cohort of 10 000 thirty-five-year-old current smokers with various smoking cessation strategies. To ensure the robustness of conclusion, univariate sensitivity analysis, probability sensitivity analysis, and age-group sensitivity analysis were conducted.Results:The results showed that varenicline intervention was the most cost-effective intervention. Compared to the next most effective option, incremental cost of each additional quality-adjusted life year is 11 140.28 yuan, which is below the threshold of willingness to pay (1 year GDP per capita). The value of ICER increased as the increasing age group of adopting intervention, but neither exceeded the threshold of willingness to pay. One-way sensitivity analysis showed that the value of discount rate, the hazard ratio and cost of intervention strategy had a greater impact on the result of ICER.Conclusion:In China, the use of varenicline to quit smoking is highly cost effective in the context of cancer primary prevention, especially for younger smokers.