Quality of life and Its Determinants among Cervical Cancer Patients in South India.

INTRODUCTION: Cervical Cancer is the leading cause of morbidity and mortality in India. It affects the patient's, physical and psychological state which results in lower quality of life (QoL). Women with cervical cancer may require counselling and time to enable them to deal with the disease and its treatment. The present study aimed to determine the quality of life and its determinants among cervical cancer patients. METHODS: A cross-sectional study was undertaken from April 2017 to September 2017 in a regional cancer centre in South India. Cervical cancer patients (N= 210) with histological confirmation were interviewed at the hospital. European Organization of Research and Treatment of Cancer (EORTC) questionnaire core module, QLQ-C30 Version 3.0, and recommended scoring algorithm were used to measure and analyse QoL. The Association of socio-economic determinants on quality of life was evaluated using multiple logistic regression. RESULTS: Among 210 cervical cancer patients enrolled, the majority 106 (50.5%) of women were between the age group 46 to 59 years and most, i.e.  167(63.0%) were not literate. The median score in the global health status was 50.0[IQR 33.3 - 66.7], 66.7[IQR 60.0 - 80.0] in physical functioning, and 83.3[IQR 66.7 - 83.3] in pain symptoms respectively which were poor compared to reference score of EORTC for all normal females and those with any cancer. The factors which were significantly associated with the GHS QoL score were the advanced stage of disease (OR:2.1, 95%CI: 1.1 - 3.9) and the age of the patients ≥60 years compared with ≤ 45 years (OR:18.4, 95%CI: 6.8 - 50.1). CONCLUSION: Cervical cancer patients had poor global health status compared to the reference score for all females with any cancer and the normal females. Advanced stage of cancer and older age have a significant association with QoL.

Time from Self-Detection of Symptoms to Seeking Definitive Care among Cervical Cancer Patients.

BACKGROUND: India had the burden of 97,000 new cases of cervical cancer with 60,000 deaths accounting nearly one-third of global cervical cancer deaths during the year 2018. Cervical cancer is the leading cause of cancer mortality in India. The present study aims to estimate the time interval between self-detection of cervical cancer symptoms and seeking care and different barriers for the possible time lag in seeking care. METHODS: A cross-sectional study was undertaken from April 2017 to September 2017 in a regional cancer centre in the south of India. The centre has both a population and a hospital-based cancer registry. Cervical cancer cases (N= 210) with histological confirmation were interviewed at the hospital using a pre-tested semi-structured questionnaire. RESULTS: The median time interval between the self-detection of cervical cancer symptoms and first contact with the general physician was 80 [IQR 45-150] days. The overall median time interval between the self-detection of symptoms to the initiation of primary treatment was 123[IQR 83-205] days. The major perceived reason for not seeking medical care was a lack of awareness in identifying cervical cancer symptoms in 183(92.9%) women. CONCLUSION: The median time of 80 days was observed from the self-detection of cervical cancer symptoms to the first contact with a general physician. Lack of awareness of patients pertaining to cancer symptoms was the major concern in seeking cancer care.
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Time Interval between Self-Detection of Symptoms to Treatment of Breast Cancer.

BACKGROUND: In India breast cancer is the number one cancer among females with an incidence rate of 25.8 per 100,000 women and mortality of 12.7 per 100,000 women. India continues to have a low 5-year survival rate of breast cancer with only 66.1% as compared to 90% in developed countries. The major reason for low survival is that patients are diagnosed with cancer at high stage. The present study attempts to delineate the time interval between self-detection of breast cancer symptoms and seeking care and to find the main reasons for delay in seeking care. METHODS: A cross sectional study was undertaken from October 2016 to March 2017 in a population based cancer registry (PBCR) and hospital based cancer registry (HBCR) located in south of India. Histologically confirmed breast cancer patients (N=181) were interviewed at hospital using a pre-tested semi structured questionnaire. RESULTS: The median time interval between the self-detection of breast cancer symptoms and first contact with general physician was 60 [IQR 30-180] days. The median time to diagnosis from the first contact was 30 [IQR 10 - 60] days and the overall median time span from self-detection of symptoms to treatment was 150 [IQR 95-265] days. The major reason given for not seeking medical care in time was lack of awareness in identifying the cancer symptoms both among patients and primary care providers. CONCLUSION: There was considerable delay from self-detection of symptoms to cancer specific primary treatment of breast cancer. We found lack of awareness among patients as well as in primary care providers to be the major concern for delay. Awareness among the target population and health care professionals would have to be improved for early diagnostics and access to care.
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Patterns of Relative Telomere Length is Associated With hTERT Gene Expression in the Tissue of Patients With Breast Cancer.

BACKGROUND: Homeostasis of telomere in breast cancer might be altered as a result of cumulative effects of various factors causing genomic instability and affecting prognosis. This study aimed to compare the relative telomere length (RTL) and hTERT mRNA expression in the tissue of patients with breast cancer along with the clinicopathologic parameters. PATIENTS AND METHODS: Frozen tumor tissues and adjacent normal breast tissue from 98 patients with invasive ductal breast cancer were used for the analysis. RTL and hTERT mRNA expression were measured using quantitative real time polymerase chain reaction. RESULTS: Among the 98 cases, 51% had an early-stage carcinoma, 66% were tumor size < 5 cm, 30% were node-negative, and 20% were low-grade tumors. In this study, 63% of cases showed higher hTERT gene expression with an odds ratio of 2.77 (P = .02). The median RTL for elongated telomere was 3.49, and the value was significantly elevated when compared with the shorter telomere. Shortened RTL was present in 60% of early-stage cancer cases, 55% where the tumor size was < 5 cm, 72% of the lymph node-negative cases, and 68% of low-grade carcinoma. Significantly elongated RTL, with median 4.22, 3.19, 3.17, and 3.28 was observed (P < .05) in the advanced stage, larger tumor size, node-positive, and high-grade cases respectively. CONCLUSION: In this study, shortened telomere was observed in early-stage cancer, and elongated telomere was found in advanced diseases. However, 13% of patients with lower hTERT gene expression showed elongated telomeres, indicating relative telomere length measurement in tissue is different from blood leukocyte, showing the dynamic process of tumorigenesis in tissue.

Assessment of Adaptive Breast Cancer Screening Policies for Improved Mortality Reduction in Low to Middle Income Countries

Objective: To investigate adaptive breast cancer screening policies using clinical breast examination for early detection and mortality reduction in low to middle income countries like India. Methods: Using published data from the Mumbai randomized cluster control trial (1998-2006), we first estimated the mean sojourn time at 5.9 years (95% Confidence Interval: 5.3-6.5) assuming 52% sensitivity of the test. The estimated mean sojourn time was used as a "silent interval" in time varying cellular kinetics with the two stage deterministic clonal expansion model, and we found age specific sojourn times in years as follows: 35-39. 0.8; 40-44, 1.0; 45-49, 1.8; 50-54, 3.2; and 55+, 5.9. Equipped with age specific sojourn times and sensitivity, we investigate adaptive screening policies for various year age groups using different screening intervals, maintaining a constant screen count of 10 and a 6 state Markov transition model. The rationale for using a fixed number of screens was to benchmark the effect of the screening interval. Result: We found that annual screening at ages 35-39 and biennial from 41-49 would achieve a mortality reduction of 27.9%, while annual screening from 38-42 and triennial from 43-58 would achieve a mortality reduction of 25.5%. Biennial screening from 40-60 years of age showed a mortality reduction of 23.6%, indicating inclusion of annual screening might be effective. We demonstrated a modelling framework that could be applied to the final data of randomized controlled trials, such as the ongoing Mumbai and Trivandrum trials in India, for assessing efficacy of annual screening in younger women. Conclusion: The framework could be useful to decide age groups that would yield maximal effectiveness in screening trials with selected screening intervals. Further, the framework could be adapted in other low to middle income countries for designing either screening trials or adaptive screening policies.