Highlights
- • Breast and cervical cancers are the two most common cancers among Indian women .
- • There was a significant increase in breast cancer while decrease in cervical cancer among all PBCRs over 25–30-year period.
- • Controlling modifiable risk factors associated with the cancers and implement the intervention of screening, vaccination, early detection and prompt treatment .
Abstract
Background
Trend analysis in cancer quantifies the incidence rate and explains the trend and pattern. Breast and cervical cancers are the two most common cancers among Indian women which contributed 39.4 % to the total cancer in India for the year 2020. This study aimed to report the time trends in cancer incidence of breast and cervical cancer using Age–Period–Cohort (APC) model from five Population Based Cancer Registries (PBCRs) in India for the period of 1985–2014.
Method
Age-Period-Cohort model was fitted to five PBCRs of Bangalore, Chennai, Delhi, Bhopal and Barshi rural for breast and cervical cancer for 25−74 age-groups. The Estimated Annual Percent Change (EAPC) was calculated. Rate Ratio (RR) of cohort effects were estimated with a constraint of period slope to be zero (p = 0) since cohort has a stronger association with incidence than period.
Result
A significant increase was noted in breast cancer in all PBCRs (EAPC, Range: Delhi, 1.2 % to Bangalore, 2.7 %) while significant decrease in cervical cancer (EAPC, Range: Bangalore -2.5 % to Chennai, -4.6 %) from all the PBCRs including Barshi rural during the period. RR estimates for breast cancer showed increasing trend whereas cervical cancer showed decreasing trend in successive birth cohorts across all five PBCRs.
Conclusion
In both breast and cervical cancers, a significant age, cohort and period effect was noted in Bangalore, Chennai and Delhi. Despite period effect, the cohort effect was predominant and it may be attributed to the generational changes in risk factors among cancer breast and cervix.
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Introduction
Globally, breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of death, and cervical cancer (CC) ranks fourth for both incidence and mortality [ ]. Breast and cervical cancers are the two most common cancers among Indian women which contributed 39.4 % to the total cancer in India for the year 2020 [ ]. In India, the systematic collection of cancer data is being carried by the Population Based Cancer Registries (PBCR) established since 1981 under the National Cancer Registry Programme (NCRP) – National Centre for Disease Informatics and Research (NCDIR) of Indian Council of Medical Research (ICMR), (ICMR-NCDIR-NCRP), Bengaluru. According to the recently released NCRP 2020 report, BC, Age Adjusted Incidence Rate (AAR) per 100,000 population was high in metro and urban cities ranging from 48.0 (Hyderabad) to 7.0 (Meghalaya). AAR of CC was high in the northeast region followed by Bangalore and Barshi rural of India. It ranged from 27.7 (Papumpare district) to 4.8 (Dibrugarh) [ ].
Trend analysis in cancer quantifies the incidence rate and explains the trend and pattern (upward or downward). It helps in evaluating primary and secondary preventive measures as well as for helathcare planning purposes [ ]. Population based cancer rates were often summarised by period/year of diagnosis and graphically presented as age-specific rate for a specific time period. However, these outcomes adjust for age in a given period and ignore the cohort effect which is an important factor in understanding time trends in cancer [ ]. Previous publication on trends in cancer incidence of specific anatomical sites from ICMR-NCDIR-NCRP was based on the Joinpoint regression model and this does not consider the birth cohort effect [ , ]. Age-Period-Cohort (APC) analysis is to differentiate and statistically estimate the unique effects associated with age, period and cohort [ ]. It has been widely used globally to measure the trends in cancer incidence rates [ ]. A few studies published from India were using APC model based on data from single PBCR [ ]. Multiplicative risk model helps to identify the variation in cancer incidence rates with regard to age effect or period effect or cohort effect or with combinations [ , ].
This paper reports the time trends in cancer incidence of breast and cervical cancer using the APC model for the composite period of 1985–2014 from five PBCRs in India.
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