Study area and period
The study was done in the oncologic unit of Dessie Comprehensive Specialized Hospital (DCSH) from March 20, 2018 to March 20, 2023. Currently, it has over 303 administrative and over 562 health workers. It also provides preventive, curative, and rehabilitative services, including oncology services, for over 8 million people. Dessie's comprehensive specialized hospital oncology unit provides treatment for about 1600 cancer patients, among whom 392 were diagnosed with CRC.
Study design
Hospital-based cross-sectional study was employed.
Population
The source population were all patients with colorectal cancer who were attending their treatment in the oncologic unit of Dessie Comprehensive Specialized Hospital. The study population were all patients with colorectal cancer who attended their treatment follow-up in the oncologic unit of Dessie Comprehensive Specialized Hospital from March 20, 2018 to March 20, 2023.
Inclusion and exclusion criteria
All patients with colorectal cancer who were attending their treatment follow-up from March 20,2018 to March 20, 2023, in the oncologic unit of Dessie Comprehensive specialized hospital were included in the study. The study excluded charts which were not recorded the status of outcome variable.
Sample size determination
The sample size for the first objective was determined using a single population proportion formula by considering the following assumptions: proportion of advanced stage presentation of CRC = 83.1%[10], 95% confidence level, and margin of error = 4%.
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)
N = 337= 337+5% (non-retrieval rate) =354
Sample size for the second objective was calculated by using Epi info STAT Calc, but the largest sample size was obtained from the first objective. There for, after adding 5% non-retrieval rate the final sample size was 354.
Sampling technique
The total number of CRC patients in the DCSH oncology unit was identified from the registration book, and then, using simple random sampling techniques, the required sample size was selected by lottery method.
Data collection tool and procedure
Data were extracted using a pre-tested and structured data abstraction sheet adapted from different literatures. The abstraction sheet was developed in English and contains socio-demographic data, including age, sex, marital status, place of residence, insurance status, educational status, and clinicopathological characteristics of the patients, such as treatment modality, recurrence history of the disease, level of Carcinoembryonic antigen (CEA) and hemoglobin, and other variables traced from the patient’s medical record charts. The data were accessed from April 21st, 2023 till May 10, 2023. The authors accessed information that identified during the data collection period.
Variables
Dependent variable: Colorectal cancer prognosed to advanced stage (Yes, no)
Independent variables
- Socio demographic and patient related factor: Age, Sex, Place of residence, Religion, Marital status, educational status, and ethnicity, and insurance status.
- personal and life style-related factors: Cigarette smoking, Chat chewing and Alcohol consumption., red meat consumption, physical exercise, weight and height
- Clinicopathological and Treatment related factors: Treatment modality, patient delay, diagnosis delay, delay to seek treatment, treatment adherence level, recurrence history after treatment, histological type, histological grading, metastasis history, primary site of the tumor, base line CEA level, anemic status and history of comorbidities.
Operational definitions
Colorectal cancer: is a disease in which cells in the colon or rectum grow out of control [11].
Advanced stage: patients with colorectal cancer diagnosed to the disease stage of III and IV [11].
Early-stage: patients with colorectal cancer diagnosed to the disease stage of I and II [12].
Comorbidity illness: any disease which is listed in the Charlson comorbidity index other than colorectal cancer at diagnosis[13].
Carcinoembryonic antigen: Tumor markers of gastrointestinal cancers especially colorectal cancer and classified as elevated (≥5ng/ml) and not elevated if <5 ng/ml[14].
Time to visit health facilities (symptom duration): the duration of time from perceiving of symptom for the first time up to health care visit and it is considered as delayed if a patient seeks health care visit more than or equal to 90 after the symptoms of CRC appeared [15, 16].
Time to diagnosis: the duration of time from initial health care visits up to the time when confirmed diagnosis is made, and considered as delayed if it is ≥30 days[15, 16].
Diagnosis to treatment interval (DTI): The time interval between confirmed colorectal cancer diagnosis up to the date of first treatment started, and considered as delayed if it is more than 30 days[15, 16] .
Poor-adherence: A patient were considered poor-adherence if they said ‘Yes’ for at most three questions [17].
Data quality assurance
Prior to data collection, training was given to data collectors and supervisors on questionnaire content, methods of data collection, and ethical concerns. To improve the quality of data, pretest was done on five percent (5%) of questionnaires before two weeks of actual data collection. After reviewing the result of the pretest, modification of the questionnaire was performed for clarity and completeness of the questionnaire. Continuous supervision of data gathering and daily checking of the collected data were performed by supervisors and principal investigator. After data collection, data verification was conducted visually and possible corrections were made by cross-checking the questionnaire.
Data processing and analysis
The data were initially coded, checked, and entered in Epi-Data software version 4.6.1, and then exported to Statistical Product and Service Solutions (SPSS) software version 27.0 for cleaning and statistical analysis. Descriptive statistics such as frequency mean and standard deviation were carried out to see the distribution of the participants within the variables included in the study. After cross-tabulation of each explanatory variable with the outcome variable, a binary logistic regression analysis model was used. Model fitness was checked using the Hosmer and Lemeshow tests. Initially, bivariable logistic regression analysis was carried out to select variables for multivariable analysis. Variables with a P value less than 0.25 in the bivariable analysis were selected as candidates for the multivariable logistic regression analysis model. Multi-collinearity among the explanatory variables was checked using the variance inflation factor and tolerance rate. To identify significant factors, multivariable binary logistic regression was conducted using the backward LR method. The level of statistical significance was declared at a P-value less than 0.05. An adjusted odds ratio with its 95% CI was used to show the strength and direction of association between each explanatory variable and the outcome variable.