Trends and Age-Period-Cohort Effects on the Incidence and Mortality Rate of Cervical Cancer in Korea

Eun-Kyeong Moon; Chang-Mo Oh; Young-Joo Won; Jong-Keun Lee; Kyu-Won Jung; Hyunsoon Cho; Jae Kwan Jun; Myong Cheol Lim; Moran Ki

doi:10.4143/crt.2016.316

Articles

Page Path: HOME > Cancer Res Treat > Volume 49(2); 2017 > Article

Original Article Trends and Age-Period-Cohort Effects on the Incidence and Mortality Rate of Cervical Cancer in Korea: Eun-Kyeong Moon, MPH¹, Chang-Mo Oh, MD, PhD^1,, Young-Joo Won, PhD^1,2,, Jong-Keun Lee, MD, PhD¹, Kyu-Won Jung, MS¹, Hyunsoon Cho, PhD^1,2, Jae Kwan Jun, MD, PhD^2,3, Myong Cheol Lim, MD, PhD^2,4,5, Moran Ki, MD, PhD²; Cancer Research and Treatment : Official Journal of Korean Cancer Association 2017;49(2):526-533.
DOI: https://doi.org/10.4143/crt.2016.316
Published online: September 1, 2016

¹Cancer Registration and Statistics Branch, National Cancer Control Institute, National Cancer Center, Goyang, Korea

²Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea

³Cancer Information and Education Branch, National Cancer Control Institute, National Cancer Center, Goyang, Korea

⁴Center for Uterine Cancer, National Cancer Center Hospital, National Cancer Center, Goyang, Korea

⁵Gynecologic Cancer Branch, National Cancer Center Hospital, National Cancer Center, Goyang, Korea

Correspondence: Young-Joo Won, PhD Cancer Registration and Statistics Branch, National Cancer Control Institute, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang 10408, Korea
Tel: 82-31-920-2015 Fax: 82-31-920-2179 E-mail: astra67@ncc.re.kr

Co-correspondence: Chang-Mo Oh, MD, PhD Cancer Registration and Statistics Branch, National Cancer Control Institute, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang 10408, Korea
Tel: 82-31-920-2971 Fax: 82-31-920-2179 E-mail: kachas@ncc.re.kr

• Received: July 16, 2016 • Accepted: August 15, 2016

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

14,684 Views
351 Download
35 Web of Science
35 Crossref
35 Scopus

prev next

Full Article

Download PDF

Abstract

Purpose
This study was conducted to describe the trends and age-period-cohort effects on the incidence and mortality rate of cervical cancer in Korea.
Materials and Methods
The incidence and mortality rate of cervical cancer among ≥ 20-year-old women from 1993 to 2012 were obtained from the Korea Central Cancer Registry and the Korean Statistical Information Service. Age-standardized rates were calculated and Joinpoint regression was used to evaluate the trends in the incidence and mortality rate. Age-period-cohort analysis was performed to investigate the independent effects of age, period and cohort.
Results
The incidence of cervical cancer decreased from 32.8 per 100,000 in 1993 to 15.9 per 100,000 in 2012 (annual percent change [APC], –3.9%; 95% confidence interval [CI], –4.2% to –3.6%). The mortality rate decreased from 5.2 per 100,000 in 1993 to 2.1 per 100,000 in 2012 (APC, –4.8%; 95% CI, –5.1% to –4.4%); however, the incidence and mortality rates among young women (< 30 years old) increased. An age-period-cohort model of the incidence and mortality rate showed decreasing period effects between 1993 and 2008 and decreasing cohort effects between 1928 and 1973, while birth cohorts after 1973 exhibited slight increases in the incidence and mortality rate of cervical cancer.
Conclusion
Recent decreases in the incidence and mortality rate of cervical cancer were due to decreases in the period and cohort effects, which reflect the implementation of a cancer screening program and changes in lifestyle. However, our findings also highlighted an increase in cohort effects on the incidence and mortality rate among young women born after 1973.
Key words: Uterine cervical neoplasms, Incidence, Mortality, Age-period-cohort analysis, Trends

Introduction

In Korea, the incidence and mortality rate of invasive cervical cancer have decreased since the introduction of a national cervical cancer screening program [1]. However, it has been suggested that the incidence of cervical cancer among young Korean women has increased during the last two decades [2]. Furthermore, changes in sexual behavior and the prevalence of human papillomavirus (HPV) infection among Korean women have also been reported [3,4]. Accordingly, age-period-cohort analysis could help separate the independent effects of age, period and cohort from trends in cancer rates [5]. Moreover, period effects reflect the factors that influence all age groups simultaneously, such as implementation of a screening program, while cohort effects reflect changes in lifestyle or external environmental exposures. To the best of our knowledge, only one Korean study has examined the trends and age-period-cohort effects on cervical cancer-related mortality [6], and that study did not evaluate incidence data and used mortality data that are now > 10 years old. Therefore, the present study was conducted to describe secular trends in the incidence and mortality rate of cervical cancer in Korea, and to use age-period-cohort analysis to evaluate these factors’ independent effects.

Materials and Methods

1. Data sources

Data regarding the incidence of cervical cancer between 1993 and 2012 were derived from the Korea National Cancer Incidence Database (KNCIDB) of the Korea Central Cancer Registry (KCCR). The KNCIDB was launched by the Korean Ministry of Health and Welfare in 1980, and is a nationwide hospital-based cancer registry. The KCCR collects data regarding approximately 80%-90% of cancer cases each year from > 180 training hospitals throughout the country [7]. Since 1999, the KCCR has covered the entire population under the population-based cancer registry program. The KNCIDB includes information regarding age, sex, diagnosis date, geographical region, histological type, primary site, and first treatment modality. Detailed information regarding the KNCIDB have been previously reported [8]. Data regarding cervical cancer-related mortality between 1993 and 2012 were obtained from Statistics Korea (http://kosis.kr). Patient records were anonymized and de-identified prior to analysis.

Ethical approval for the research protocol was provided by the Institutional Review Board of the National Cancer Center, Goyang, Korea (NCC2015-0185).

2. Adjusting the cervical cancer-related mortality

Although the incidence data has high quality and completeness, the majority of mortality data for cervical cancer has been recorded as unspecified uterine cancer deaths [6,9]. Therefore, it is necessary to redistribute unspecified uterine cancer deaths to cervical cancer deaths using a redistribution algorithm estimation of more accurate cervical cancer mortality trends. To accomplish this, we linked the incidence database with the mortality database, then extracted registered cases of malignant neoplasms of the cervix uteri (C53) among deaths from unspecified malignant neoplasms of the uterus (C55) based on the tenth edition of the International Classification of Diseases [10]. For the present study, we adjusted the numbers of cervical cancer-related deaths (C53) using the proportion of registered cases of cervical cancer (i.e., incidence, ‘C53’) to the number of deaths due to unspecified uterine cancer (C55) in each age group. The detailed redistribution algorithm has been documented in a previous report [6].

3. Statistical analysis

We excluded the incidence and mortality data from < 20-year-old women because the numbers of cases and cancer-related deaths were very low. The incidence and mortality rates of cervical cancer were grouped into thirteen age groups (most age groups covered 5 years; 20-24 years old, …, ≥ 80 years old). The incidence and mortality data were also arranged in four 5-year periods from 1993-1997 to 2008-2012. The age-standardized incidences and mortality rates were calculated using Segi’s world standard population [11]. The Joinpoint regression analysis program was employed to estimate trends in the age-standardized incidences and mortality rates [12], and the results were expressed as the annual percent changes (APCs) and their 95% confidence intervals (CIs) for each period. Age-period-cohort effects were assessed using a log-linear model to describe trends in the incidence and mortality rate using the intrinsic estimator method [13]. The goodness of fit for each model was estimated using the likelihood ratio test and the Akaike information criterion (AIC). p-values of < 0.05 were considered statistically significant. All statistical analyses were performed using the Stata software ver. 12.0 (StataCorp LP, College Station, TX) and Joinpoint software ver. 4.1.1 (Surveillance Research Program, National Cancer Institute, Bethesda, MD).

Results

1. Trends in incidence

The age-standardized incidence of cervical cancer among ≥ 20-year-old women decreased from 32.8 per 100,000 in 1993 to 15.9 per 100,000 in 2012 (APC, –3.9%; 95% CI, –4.2% to –3.6%) (Table 1). The peak age for the incidence of cervical cancer steadily increased from 60-64 years during 1993-1997 to 75-79 years during 2008-2012 (Fig. 1A). The age-specific incidence of cervical cancer exhibited a decreasing trend for all age groups, with the exception of women who were < 30 years old and ≥ 75 years old (Fig. 1B). The incidence of cervical cancer among < 30-year-old women exhibited an increasing trend, and the APC among 20-24-year-old women (APC, 5.6%; 95% CI, 2.9% to 8.3%) was greater than that among 25-29-year-old women (APC, 2.5%; 95% CI, 1.4% to 2.5%) (data not shown).

2. Trends in mortality rates

The age-standardized mortality rate for cervical cancer among ≥ 20-year-old women decreased from 5.2 per 100,000 in 1993 to 2.1 per 100,000 in 2012 (APC, –4.8%; 95% CI, –5.1% to –4.4%) (Table 1). As shown in Fig. 2A, the mortality rate for cervical cancer increased with age, except among elderly people (≥ 70 years old) during 1993-1997. The age-specific mortality rate for cervical cancer exhibited a decreasing trend for all age groups, with the exception of women who were 20-24 years old and ≥ 75 years old (Fig. 2B).

3. Age-period-cohort models

The age-period-cohort model of incidence had the lowest AIC value from the goodness of fit tests (Table 2). The age-period-cohort model of mortality had the lowest AIC value, and was selected as the model with the best fit based on the goodness of fit test results (Table 2). In the age-period-cohort models, the period effects for the incidence and mortality rate of cervical cancer both decreased from 1993 to 2008 (Fig. 3A and B). The risk ratio for cervical cancer incidence and mortality decreased among women who were born between 1928 and 1973 after we adjusted for age and period effects. However, the risk ratio for cervical cancer incidence and mortality increased among women who were born after 1973.

Discussion

Our findings revealed that the incidence and mortality rate of cervical cancer decreased from 1993 to 2012. The decreasing trends in the Korean incidence and mortality rate are consistent with a pattern of decreasing trends throughout developed countries [14]. Our age-period-cohort models also suggest that the decrease in the period and cohort effects significantly contributed to decreases in the incidence and mortality rate of cervical cancer. However, the incidence and mortality rate of cervical cancer gradually increased in the younger birth cohorts, and the recent birth cohort effects (after the 1973 birth year) also exhibited an increasing trend.

1. Cohort effect

The decreasing cohort effects on the incidence and mortality rate among women who were born from 1928-1973 could be explained by improvements in their socioeconomic status, access to hospital-based treatment, and cervical cancer screening program [15]. Furthermore, the cohort effect that we observed was similar to that reported in Mumbai [16]. In this context, lower socioeconomic status is highly associated with the risk of HPV infection, which is a major risk factor for cervical cancer [17]. Thus, the economic growth in Korea may have resulted in improved access to hospital-based treatments and greater coverage for the cervical cancer screening program. However, the risk ratio for cervical cancer incidence and mortality exhibited an increasing trend among younger cohorts. There are some possible explanations for the increased cervical cancer incidence and mortality among young women in Korea. Specifically, sexual behavior in younger cohorts has changed compared with older cohorts and the age at first intercourse has become earlier [3]. These changes in sexual behavior may have led to the increased prevalence of HPV infection in more recent Korean birth cohorts [4]. Additionally, there have been changes in the nature of cervical cancer in young women. For example, in situ adenocarcinoma or adenocarcinoma has increased among young women in western countries [18-20]. In Korea, adenocarcinoma increased from 1993 to 2001 among young women aged 20-29 years old [1]. Adenocarcinoma is usually located in the cervical canal; therefore, it was relatively hard to detect in cervical cancer screening compared to squamous cell carcinoma [21]. Indeed, it was reported that the proportion of the lymph node metastasis and tumor size have increased among young women aged < 35 years old in Korea [22]. Finally, young women have a relatively low screening rate for cervical cancer and this rate showed slight decreasing trends among women aged 30-39 years old [23]. Taken together, these factors have likely contributed to the rise in incidence and mortality of cervical cancer among young women in Korea.

2. Period effect

Cervical cancer screening programs are effective and powerful tools that can reduce the risk of cervical cancer and prevent cervical cancer-related deaths. For example, the implementation of cervical cancer screening programs has decreased the incidence and mortality rate of cervical cancer in Europe and North America [14,24], as well as in Asia [25,26]. Based on the age-period-cohort analysis results, period effects imply that this screening has beneficial effects [14]. However, using period effects as a surrogate marker for the screening effects assumes that the cervical cancer screening was implemented at the same time in all age groups. Although the Korea screening program was implemented in 1996, not all age groups received free access to the program at the same time [1]. In addition, the participation rate varies according to age group [6,23]. Thus, differences in the participation rates may have resulted in the cohorts affecting the cervical cancer incidence and mortality rather than the periods, which were considered a surrogate marker for the screening effects [14].

3. Strengths and limitations

Our results were internally consistent with the incidence and mortality rate of cervical cancer. In addition, our study population represents the entire population of Korea and our results are biologically plausible based on the results from other studies [16,27]. Nevertheless, this study has several limitations that warrant consideration. First, the completeness of the incidence data from before 1999 may be lower than that from after 1999, and this discrepancy may have introduced bias into our estimated trends and age-period-cohort effects. However, the incidence data from after 1993 were collected by the Gynecologic Oncology Committee of Korea, which launched a gynecological cancer registry in 1991, and it is likely that there were very few discrepancies between the data from 1993-1998 and the data from 1999-2012. Second, the early mortality data are less reliable, and the validity of the cervical cancer-related mortality data would be expected to increase over time. Therefore, we adjusted these data by matching the mortality data with the cancer registry data using a redistribution algorithm. Nevertheless, it is possible that residual errors were included in the cervical cancer-related mortality data, despite the use of the redistribution algorithm. Third, age-period-cohort models always have an internal limitation that is related to identifiability. However, the intrinsic estimator method is a variant of the principal components regression method that provides an unbiased estimation and has a smaller variance than constrained models [28].

Conclusion

The present study revealed that the incidence and mortality rate of cervical cancer in Korea have decreased since 1993. This recent decrease in the incidence and mortality rate of cervical cancer may be due to decreases in the period and cohort effects, which likely reflect the implementation of a Korean cancer screening program and changes in lifestyle. However, the risks of cervical cancer incidence and mortality tended to increase in the younger cohorts. These findings suggest that a more effective cervical cancer prevention program is required for younger Korean women, such as HPV vaccination, which may be a useful tool for preventing cervical cancer among this population.

NOTES

Conflict of interest relevant to this article was not reported.

Acknowledgements

This work was supported by a research grant from the National Cancer Center, Republic of Korea (No. 1610201-1).

Fig. 1.

Incidence rates of cervical cancer. (A) The age-specific incidences rates of cervical cancer according to time period; each line connects the age-specific incidence for a 5-year period. (B) The birth cohort–specific incidence rates of cervical cancer according to age group; each line connects the birth cohort–specific incidence for a 5-year age group.

Fig. 2.

Mortality rates for cervical cancer. (A) The age-specific mortality rates of cervical cancer according to time period; each line connects the age-specific mortality rate for a 5-year period. (B) The birth cohort–specific mortality rates for cervical cancer according to age group; each line connects the birth cohort–specific mortality rate for a 5-year age group.

Fig. 3.

Age-period-cohort analysis of cervical cancer. (A) The incidences of cervical cancer in Korea. The blue line indicates the age effect and 95% confidence interval, the red line indicates the period effect and 95% confidence interval, and the green line indicates the cohort effect and corresponding 95% confidence interval. (B) The mortality rates for cervical cancer in Korea. The blue line indicates the age effect and 95% confidence interval, the red line indicates the period effect and 95% confidence interval, and the green line indicates the cohort effect and corresponding 95% confidence interval.

Table 1.

Joinpoint regression analysis of trends in the incidence and mortality rate of cervical cancer

Category	ASR		APC (95% CI)
Category	1993	2012	APC (95% CI)
Incidence	32.8	15.9	–3.9 (–4.2 to –3.6)^*
Mortality	5.2	2.1	–4.8 (–5.1 to –4.4)^*

The Joinpoint regression model was used to test whether age-standardized rates have significantly changed. The trends in cervical cancer rates were summarized as APC.

ASR, age-standardized rate per 100,000 women (adjusted for Segi’s world standard population); APC, annual percent change; CI, confidence interval.

^* p < 0.05.

Table 2.

Goodness of fit for the age-period-cohort models of cervical cancer incidence and mortality in Korea

Model	Incidence				Mortality
Model	df	Log-likelihood	AIC	p-value^a)	df	Log-likelihood	AIC	p-value^a)
Age	39	–2,888.1	111.6	< 0.01	39	–1,294.2	50.3	< 0.01
Period	48	–20,333.4	782.2	< 0.01	48	–13,631.6	524.4	< 0.01
Cohort	36	–4,478.8	172.9	< 0.01	36	–650.0	25.6	< 0.01
Age+period	36	–927.1	36.3	< 0.01	36	–608.0	24.0	< 0.01
Age+cohort	24	–257.8	11.0	0.02	24	–224.2	9.7	< 0.01
Period+cohort	33	–4,407.7	170.3	< 0.01	33	–612.8	24.3	< 0.01
Age+period+cohort (intrinsic estimator)	22	–253.9	10.9		22	–218.2	9.5

df, degrees of freedom; AIC, Akaike information criterion.

^a) p-values were calculated using the likelihood ratio test.

REFERENCES

1. Oh CM, Jung KW, Won YJ, Shin A, Kong HJ, Jun JK, et al. Trends in the incidence of in situ and invasive cervical cancer by age group and histological type in Korea from 1993 to 2009. PLoS One. 2013;8:e72012Article PubMed PMC
2. Lim MC, Moon EK, Shin A, Jung KW, Won YJ, Seo SS, et al. Incidence of cervical, endometrial, and ovarian cancer in Korea, 1999-2010. J Gynecol Oncol. 2013;24:298–302. Article PubMed PMC
3. Kim CJ, Kim BG, Kim SC, Kim YT, Kim YM, Park SY, et al. Sexual behavior of Korean young women: preliminary study for the introducing of HPV prophylactic vaccine. Korean J Gynecol Oncol. 2007;18:209–18. Article
4. Kim YT. Current status of cervical cancer and HPV infection in Korea. J Gynecol Oncol. 2009;20:1–7. Article PubMed PMC
5. Clayton D, Schifflers E. Models for temporal variation in cancer rates. I: Age-period and age-cohort models. Stat Med. 1987;6:449–67. Article PubMed
6. Shin HR, Park S, Hwang SY, Kim JE, Jung KW, Won YJ, et al. Trends in cervical cancer mortality in Korea 1993-2002: corrected mortality using national death certification data and national cancer incidence data. Int J Cancer. 2008;122:393–7. Article PubMed
7. Jung KW, Won YJ, Kong HJ, Oh CM, Cho H, Lee DH, et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2012. Cancer Res Treat. 2015;47:127–41. Article PubMed PMC PDF
8. Shin HR, Won YJ, Jung KW, Kong HJ, Yim SH, Lee JK, et al. Nationwide cancer incidence in Korea, 1999~2001; first result using the national cancer incidence database. Cancer Res Treat. 2005;37:325–31. Article PubMed PMC PDF
9. Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H, et al. Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer. 2013;49:1374–403. Article PubMed
10. World Health Organization. International statistical classification of diseases and related health problems. 10th ed. Geneva: World Health Organization; 1994.
11. Segi M, Fujisaku S. Cancer mortality for selected sites in 24 countries (1950-1957). Sendai: Tohoku University Press; 1960.
12. National Cancer Institute. Joinpoint regression program version 3.5.3 [Internet]. Bethesda, MD: National Cancer Institute; 2012. [cited 2015 Aug 20]. Available from: http://surveillance.cancer.gov/joinpoint/
13. Yang Y, Schulhofer‐Wohl S, Fu WJ, Land KC. The intrinsic estimator for age‐period‐cohort analysis: what it is and how to use it. Am J Sociol. 2008;113:1697–736. Article
14. Vaccarella S, Franceschi S, Engholm G, Lonnberg S, Khan S, Bray F. 50 years of screening in the Nordic countries: quantifying the effects on cervical cancer incidence. Br J Cancer. 2014;111:965–9. Article PubMed PMC
15. Parkin DM, Bray FI, Devesa SS. Cancer burden in the year 2000: the global picture. Eur J Cancer. 2001;37 Suppl 8:S4–66. Article PubMed
16. Dhillon PK, Yeole BB, Dikshit R, Kurkure AP, Bray F. Trends in breast, ovarian and cervical cancer incidence in Mumbai, India over a 30-year period, 1976-2005: an age-period-cohort analysis. Br J Cancer. 2011;105:723–30. Article PubMed PMC
17. Benard VB, Johnson CJ, Thompson TD, Roland KB, Lai SM, Cokkinides V, et al. Examining the association between socioeconomic status and potential human papillomavirus-associated cancers. Cancer. 2008;113(10 Suppl):2910–8. Article PubMed
18. Bulk S, Visser O, Rozendaal L, Verheijen RH, Meijer CJ. Cervical cancer in the Netherlands 1989-1998: decrease of squamous cell carcinoma in older women, increase of adenocarcinoma in younger women. Int J Cancer. 2005;113:1005–9. Article PubMed
19. Liu S, Semenciw R, Mao Y. Cervical cancer: the increasing incidence of adenocarcinoma and adenosquamous carcinoma in younger women. CMAJ. 2001;164:1151–2. PubMed PMC
20. Wang SS, Sherman ME, Hildesheim A, Lacey JV Jr, Devesa S. Cervical adenocarcinoma and squamous cell carcinoma incidence trends among white women and black women in the United States for 1976-2000. Cancer. 2004;100:1035–44. Article PubMed
21. International Collaboration of Epidemiological Studies of Cervical Cancer. Comparison of risk factors for invasive squamous cell carcinoma and adenocarcinoma of the cervix: collaborative reanalysis of individual data on 8,097 women with squamous cell carcinoma and 1,374 women with adenocarcinoma from 12 epidemiological studies. Int J Cancer. 2007;120:885–91. Article PubMed
22. Han CH, Cho HJ, Lee SJ, Bae JH, Bae SN, Namkoong SE, et al. The increasing frequency of cervical cancer in Korean women under 35. Cancer Res Treat. 2008;40:1–5. Article PubMed PMC PDF
23. Suh M, Choi KS, Lee YY, Jun JK. Trends in cancer screening rates among Korean men and women: results from the Korean national cancer screening survey, 2004-2012. Cancer Res Treat. 2013;45:86–94. Article PubMed PMC PDF
24. Peirson L, Fitzpatrick-Lewis D, Ciliska D, Warren R. Screening for cervical cancer: a systematic review and meta-analysis. Syst Rev. 2013;2:35.Article PubMed PMC PDF
25. Aklimunnessa K, Mori M, Khan MM, Sakauchi F, Kubo T, Fujino Y, et al. Effectiveness of cervical cancer screening over cervical cancer mortality among Japanese women. Jpn J Clin Oncol. 2006;36:511–8. Article PubMed
26. Chen YY, You SL, Chen CA, Shih LY, Koong SL, Chao KY, et al. Effectiveness of national cervical cancer screening programme in Taiwan: 12-year experiences. Br J Cancer. 2009;101:174–7. Article PubMed PMC
27. Leung GM, Woo PP, McGhee SM, Cheung AN, Fan S, Mang O, et al. Age-period-cohort analysis of cervical cancer incidence in Hong Kong from 1972 to 2001 using maximum likelihood and Bayesian methods. J Epidemiol Community Health. 2006;60:712–20. Article PubMed PMC
28. Yang Y, Fu WJ, Land KC. A methodological comparison of age‐period‐cohort models: the intrinsic estimator and conventional generalized linear models. Sociol Methodol. 2004;34:75–110. Article

Figure & Data

REFERENCES

Citations

Citations to this article as recorded by

Trends in gynecological cancer incidence, mortality, and survival among elderly women: A SEER study
Subhadra Priyadarshini, Prafulla Kumar Swain, Khushi Agarwal, Diptismita Jena, Sourav Padhee
AGING MEDICINE.2024; 7(2): 179. CrossRef
Determination of ovarian transposition through prediction of postoperative adjuvant therapy in young patients with early stage cervical cancer undergoing surgery: a Korean multicenter retrospective study (KGOG 1042)
Woo Yeon Hwang, Chel Hun Choi, Kidong Kim, Moon-Hong Kim, Myong Cheol Lim, Banghyun Lee, Myounghwan Kim, Yun Hwan Kim, Seok Ju Seong, Jong-Min Lee
Obstetrics & Gynecology Science.2024; 67(3): 296. CrossRef
Global, regional, and national trends in mesothelioma burden from 1990 to 2019 and the predictions for the next two decades
Wenmin Zhu, Jialin Liu, Yiling Li, Ziwei Shi, Sheng Wei
SSM - Population Health.2023; 23: 101441. CrossRef
Changes in cervical dysplasia, carcinoma in situ, and cervical cancer after expanding the National Cancer Screening Program to younger women in Korea
Woorim Kim, Sungyoun Chun, Sang Ah Lee
International Journal for Quality in Health Care.2023;[Epub] CrossRef
Secular trend in disease burden of leukemia and its subtypes in China from 1990 to 2019 and its projection in 25 years
Dongdong Niu, Yumei Zhao, Jia Wang, Enlin Ye, Jiasheng Huang, Jie Liu, Xueying Huang, Suru Yue, Xuefei Hou, Jiayuan Wu
Annals of Hematology.2023; 102(9): 2375. CrossRef
Gigantol inhibits proliferation and enhanced oxidative stress‐mediated apoptosis through modulating of Wnt/β‐catenin signaling pathway in HeLa cells
Huanan Kang, Yiming Sun, Xijiao Hu, Li Liu
Journal of Biochemical and Molecular Toxicology.2022;[Epub] CrossRef
Antiproliferative and apoptotic potential of Glycyrrhizin against HPV16+ Caski cervical cancer cells: A plausible association with downreguation of HPV E6 and E7 oncogenes and Notch signaling pathway
Afza Ahmad, Rohit Kumar Tiwari, Prakriti Mishra, Ali G. Alkhathami, Tahani M. Almeleebia, Mohammad Y. Alshahrani, Irfan Ahmad, Rawan Amer Asiri, Noura M. Alabdullah, Mohamed Hussien, Mohd Saeed, Irfan Ahmad Ansari
Saudi Journal of Biological Sciences.2022; 29(5): 3264. CrossRef
Trends in cervical cancer screening rates among Korean women: results of the Korean National Cancer Screening Survey, 2005–2020
Hye Young Shin, Yun Yeong Lee, Soo Yeon Song, Bomi Park, Mina Suh, Kui Son Choi, Jae Kwan Jun
Journal of Gynecologic Oncology.2022;[Epub] CrossRef
Disparities in the increases of cervical cancer incidence rates: observations from a city-wide population-based study
Ke Li, Huan Xu, Suixiang Wang, Pengzhe Qin, Boheng Liang
BMC Cancer.2022;[Epub] CrossRef
Inequalities in Temporal Effects on Cervical Cancer Mortality in States in Different Geographic Regions of Brazil: An Ecological Study
Karina Cardoso Meira, Carinne Magnago, Angelo Braga Mendonça, Stephane Fernanda Soares Duarte, Pedro Henrique Oliveira de Freitas, Juliano dos Santos, Dyego Leandro Bezerra de Souza, Taynãna César Simões
International Journal of Environmental Research and Public Health.2022; 19(9): 5591. CrossRef
Trends in Incidence Rates, Mortality Rates, and Age-Period-Cohort Effects of Cervical Cancer — China, 2003–2017
Kexin Sun, Rongshou Zheng, Lin Lei, Siwei Zhang, Hongmei Zeng, Shaoming Wang, Li Li, Ru Chen, Bingfeng Han, Ji Peng, Wenqiang Wei, Jie He
China CDC Weekly.2022; 4(48): 1070. CrossRef
Population-Based Temporal Trends and Ethnic Disparity in Cervical Cancer Mortality in South Africa (1999–2018): A Join Point and Age–Period–Cohort Regression Analyses
Gbenga Olorunfemi, Elena Libhaber, Oliver Ezechi, Eustasius Musenge
Cancers.2022; 14(24): 6256. CrossRef
Understanding of Cervical Screening Adoption among Female University Students Based on the Precaution Adoption Process Model and Health-Belief Model
Hye Young Shin, Purum Kang, Soo Yeon Song, Jae Kwan Jun
International Journal of Environmental Research and Public Health.2022; 20(1): 700. CrossRef
The Effects of Age, Period, and Cohort on the Mortality of Cervical Cancer in Three High‐Income Countries: Canada, Korea, and Italy
Jinyao Wang, Zhiqiang Bai, Xudong Gao, Nianping Zhang, Zhenkun Wang, Zhongjie Shi
BioMed Research International.2021;[Epub] CrossRef
Metasequoia glyptostroboides potentiates anticancer effect against cervical cancer via intrinsic apoptosis pathway
Hoomin Lee, Cheolwoo Oh, Suji Kim, Debasish Kumar Dey, Hyung Kyo Kim, Vivek K. Bajpai, Young-Kyu Han, Yun Suk Huh
Scientific Reports.2021;[Epub] CrossRef
The Trend of HIV/AIDS Incidence and Risks Associated with Age, Period, and Birth Cohort in Four Central African Countries
Nodjimadji Tamlengar Martial, Sumaira Mubarik, Chuanhua Yu
International Journal of Environmental Research and Public Health.2021; 18(5): 2564. CrossRef
Trends in breast and cervical cancer in India under National Cancer Registry Programme: An Age-Period-Cohort analysis
Krishnan Sathishkumar, Vinodh N, R.A. Badwe, S.V.S. Deo, N. Manoharan, Reeni Malik, NS Panse, C. Ramesh, Atul Shrivastava, R. Swaminathan, C.R. Vijay, Sandeep Narasimhan, Meesha Chaturvedi, Prashant Mathur
Cancer Epidemiology.2021; 74: 101982. CrossRef
Tendencias temporales del cáncer de cuello uterino invasivo en mujeres entre 20 y 39 años en Manizales, Colombia. 2003-2018
María Del Pilar Arango Arango
Revista Médica de Risaralda.2021;[Epub] CrossRef
Analysis of the effects of the age-period-birth cohort on cervical cancer mortality in the Brazilian Northeast
Karina Cardoso Meira, Glauber Weder dos Santos Silva, Juliano dos Santos, Raphael Mendonça Guimarães, Dyego Leandro Bezerra de Souza, Gilcilene Pretta Cani Ribeiro, Eder Samuel Oliveira Dantas, Jovanka Bittencourt Leite de Carvalho, Rafael Tavares Jomar,
PLOS ONE.2020; 15(2): e0226258. CrossRef
Age-Period-Cohort Analysis of HIV Mortality in China: Data from the Global Burden of Disease Study 2016
Disi Gao, Zhiyong Zou, Wenjing Zhang, Tianqi Chen, Wenxin Cui, Yinghua Ma
Scientific Reports.2020;[Epub] CrossRef
Kallikrein 5 overexpression is associated with poor prognosis in uterine cervical cancer
Jee Suk Chang, Nalee Kim, Ji-Ye Kim, Sung-Im Do, Yeona Cho, Hyun-Soo Kim, Yong Bae Kim
Journal of Gynecologic Oncology.2020;[Epub] CrossRef
Trends in cervical cancer mortality in Brazil in 5 years (2012-2016)
Blenda Tallon, Denise Monteiro, Leila Soares, Nádia Rodrigues, Flavio Morgado
Saúde em Debate.2020; 44(125): 362. CrossRef
Tendências da mortalidade por câncer de colo no Brasil em 5 anos (2012-2016)
Blenda Tallon, Denise Monteiro, Leila Soares, Nádia Rodrigues, Flavio Morgado
Saúde em Debate.2020; 44(125): 362. CrossRef
Cervical Cancer Screening and Human Papillomavirus Vaccination among Korean Sexual Minority Women by Sex of Their Sexual Partners
Ssirai Kim, Sun-Young Lee, Smi Choi-Kwon
International Journal of Environmental Research and Public Health.2020; 17(23): 8924. CrossRef
Increasing risk of uterine cervical cancer among young Japanese women: Comparison of incidence trends in Japan, South Korea and Japanese‐Americans between 1985 and 2012
Mai Utada, Pavel Chernyavskiy, Won Jin Lee, Silvia Franceschi, Catherine Sauvaget, Amy Berrington de Gonzalez, Diana R. Withrow
International Journal of Cancer.2019; 144(9): 2144. CrossRef
Ovarian transposition before radiotherapy in cervical cancer patients: functional outcome and the adequate dose constraint
Lina Yin, Saiquan Lu, Jun Zhu, Weiling Zhang, Guihao Ke
Radiation Oncology.2019;[Epub] CrossRef
Prevalence of human papillomavirus-related diseases in the Republic of Korea: a cross-sectional study
Jin-Kyoung Oh, Hwa Young Choi, Minji Han, Jae-Kwan Lee, Kyung-Jin Min, Moran Ki
Sexually Transmitted Infections.2019; 95(4): 292. CrossRef
Contributions and Limitations of National Cervical Cancer Screening Program in Korea: A Retrospective Observational Study
Jung Hyun Lee, Hyeongsu Kim, Heejung Choi, Hyoseon Jeong, Young Ko, Seung-Hyuk Shim, Eunjoo Lee, Su Hyun Chae
Asian Nursing Research.2018; 12(1): 9. CrossRef
The Prognostic Impact of the Number of Metastatic Lymph Nodes and a New Prognostic Scoring System for Recurrence in Early-Stage Cervical Cancer with High Risk Factors: A Multicenter Cohort Study (KROG 15-04)
Jeanny Kwon, Keun-Young Eom, Young Seok Kim, Won Park, Mison Chun, Jihae Lee, Yong Bae Kim, Won Sup Yoon, Jin Hee Kim, Jin Hwa Choi, Sei Kyung Chang, Bae Kwon Jeong, Seok Ho Lee, Jihye Cha
Cancer Research and Treatment.2018; 50(3): 964. CrossRef
Who Really Benefits from 3D-Based Planning of Brachytherapy for Cervical Cancer?
In Bong Ha, Bae Kwon Jeong, Ki Mun Kang, Hojin Jeong, Yun Hee Lee, Hoon Sik Choi, Jong Hak Lee, Won Jun Choi, Jeong Kyu Shin, Jin Ho Song
Journal of Korean Medical Science.2018;[Epub] CrossRef
Induction of Apoptotic Cell Death on Human Cervix Cancer HeLa cells by Extract from Loranthus yadoriki
Eun-Joo Kim, Chang-Won Kang, Nan-Hee Kim, Yong Bae Seo, Soo-Wan Nam, Gun-Do Kim
Biotechnology and Bioprocess Engineering.2018; 23(2): 201. CrossRef
Updates on Cancer Epidemiology in Korea, 2018
Sun-Seog Kweon
Chonnam Medical Journal.2018; 54(2): 90. CrossRef
The economic burden of human papillomavirus infection-associated diseases in the Republic of Korea, 2002–2015
Moran Ki, Hwa Young Choi, Minji Han, Jin-Kyoung Oh
Vaccine.2018; 36(31): 4633. CrossRef
How confident can we be in the current guidelines for exiting cervical screening?
Patti E. Gravitt, Rebecca Landy, Mark Schiffman
Preventive Medicine.2018; 114: 188. CrossRef
Comparison of gynecologic cancer risk factors, incidence and mortality trends between South Korea and Israel, 1999–2013
N Michaan, S Y Park, Y J Won, M C Lim
Japanese Journal of Clinical Oncology.2018; 48(10): 884. CrossRef

PubReader
ePub Link

Cite

CITE: export Copy Download Format; Close

Download Citation

Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

Format:

RIS — For EndNote, ProCite, RefWorks, and most other reference management software
BibTeX — For JabRef, BibDesk, and other BibTeX-specific software

Include:

Citation for the content below
Citation and abstract for the content below

Trends and Age-Period-Cohort Effects on the Incidence and Mortality Rate of Cervical Cancer in Korea

Cancer Res Treat. 2017;49(2):526-533. Published online September 1, 2016

DOI: https://doi.org/10.4143/crt.2016.316

XML Download

Abstract
Introduction
Materials and Methods
Results
Discussion
Conclusion
NOTES
REFERENCES

Trends and Age-Period-Cohort Effects on the Incidence and Mortality Rate of Cervical Cancer in Korea

Fig. 1. Incidence rates of cervical cancer. (A) The age-specific incidences rates of cervical cancer according to time period; each line connects the age-specific incidence for a 5-year period. (B) The birth cohort–specific incidence rates of cervical cancer according to age group; each line connects the birth cohort–specific incidence for a 5-year age group.

Fig. 2. Mortality rates for cervical cancer. (A) The age-specific mortality rates of cervical cancer according to time period; each line connects the age-specific mortality rate for a 5-year period. (B) The birth cohort–specific mortality rates for cervical cancer according to age group; each line connects the birth cohort–specific mortality rate for a 5-year age group.

Fig. 3. Age-period-cohort analysis of cervical cancer. (A) The incidences of cervical cancer in Korea. The blue line indicates the age effect and 95% confidence interval, the red line indicates the period effect and 95% confidence interval, and the green line indicates the cohort effect and corresponding 95% confidence interval. (B) The mortality rates for cervical cancer in Korea. The blue line indicates the age effect and 95% confidence interval, the red line indicates the period effect and 95% confidence interval, and the green line indicates the cohort effect and corresponding 95% confidence interval.

Fig. 1.

Fig. 2.

Fig. 3.

Trends and Age-Period-Cohort Effects on the Incidence and Mortality Rate of Cervical Cancer in Korea

Category	ASR		APC (95% CI)
Category	1993	2012	APC (95% CI)
Incidence	32.8	15.9	–3.9 (–4.2 to –3.6)^*
Mortality	5.2	2.1	–4.8 (–5.1 to –4.4)^*

Model	Incidence				Mortality
Model	df	Log-likelihood	AIC	p-value^a)	df	Log-likelihood	AIC	p-value^a)
Age	39	–2,888.1	111.6	< 0.01	39	–1,294.2	50.3	< 0.01
Period	48	–20,333.4	782.2	< 0.01	48	–13,631.6	524.4	< 0.01
Cohort	36	–4,478.8	172.9	< 0.01	36	–650.0	25.6	< 0.01
Age+period	36	–927.1	36.3	< 0.01	36	–608.0	24.0	< 0.01
Age+cohort	24	–257.8	11.0	0.02	24	–224.2	9.7	< 0.01
Period+cohort	33	–4,407.7	170.3	< 0.01	33	–612.8	24.3	< 0.01
Age+period+cohort (intrinsic estimator)	22	–253.9	10.9		22	–218.2	9.5

Table 1. Joinpoint regression analysis of trends in the incidence and mortality rate of cervical cancer

The Joinpoint regression model was used to test whether age-standardized rates have significantly changed. The trends in cervical cancer rates were summarized as APC.

ASR, age-standardized rate per 100,000 women (adjusted for Segi’s world standard population); APC, annual percent change; CI, confidence interval.

p < 0.05.

Table 2. Goodness of fit for the age-period-cohort models of cervical cancer incidence and mortality in Korea

df, degrees of freedom; AIC, Akaike information criterion.

p-values were calculated using the likelihood ratio test.