Factors associated with delay in the diagnosis of
Oral squamous cell carcinoma in Bangladesh
Chapter: One
Introduction
Malignant disease of the head and neck region is a significant cause of morbidity and mortality both in Bangladesh and throughout the world. In Bangladesh oral squamous cell carcinoma accounts for 20% of whole body malignancy (Molla M.R.& Shaheed Iqbal, 1996). With approximately 389000 new cases of oral cancer per year, the oral squamous cell carcinoma is the 11th most common cancer in the world (Scott et al, 2006). Oral squamous cell carcinoma is the most commonly seen malignant tumor in the oral cavity that comprises more than 80% of the oral cancer (Wei Gao and Chuan Bin Gao 2009). Its clinical stages [TNM] at diagnosis have an important influence on the survival and prognosis of patients. If lesions are detected when they are small, localized and treated expeditiously, survival rates of 70% to 90% can be achieved (Pitiphat W. et al 2002).
In Bangladesh 78% of patients with oral squamous cell carcinoma have the habit of chewing tobacco in the form of zarda or dried tobacco leaves, along with lime and betel nut. Only 12% of the patients have the habits of chewing betel nut, lime and catechu without any other ingredients or tobacco. Chewing tobacco along with lime betel nut is the most potent etiological factors for oral cancer in Bangladesh (Molla M.R. et al, 1995)
The silent nature of the lesion and delay in the diagnosis are believed to be responsible for high incidence of advanced-stage oral cancer (Scott SE et al 2005). The five years survival rate of persons with localized lesion is greater than that for those with distant metastases (Pitiphat W. et al 2002).
The five years survival rate of oral squamous cell carcinoma patients vary in relation to several factors such as age, site, and method of treatment. Available reports show a similar pattern of survival in which the higher the clinical staging, the lower the survival ( Kerdapon D.,Sriplung H.,2001)
The five years survival of oral squamous cell carcinoma is as good as 72%-86% for TNM stage I, less than 50% for TNM stage II, 27%-38% for TNM stage III and 12%- 16% for TNM stage IV (Kerdapon D.,Sriplung H.,2001).
One of the most important objectives of a public health service is early diagnosis of disease, which provides a better prognosis and reduction in treatment cost. However, numerous reports suggest that up to 50% of patients present with advanced stage disease (Scott SE et al 2005). Studies on survival of patients with oral cancer in Rio De Janirohave found a strong correlation between the increase mortality and advanced clinical stage, and highlight the importance of reducing the time between the appearance of symptoms and diagnosis, as one of the most important factors to improve prognosis (Evandro Neves Abdo et al 2007).
To develop an effective intervention to reduce the extent of delay in diagnosis it is essential to identify factors associated with delay in oral cancer. Delay in diagnosis consists of patient delay and professional delay (Aquilina Peter Joseph 2007, Kerdapon D., Sriplung H.,2001).
Patient’s delay is defined as the time interval between the perception of the 1st signs or symptoms and the initial professional evaluation (Allison P.et al, 1998).
Professional delay is defined as the time period from first consultation to a definitive diagnosis being made or referral to a specialist (Allison P.et al 1998).
It is logical to assume that there would be a simple relation between delay in diagnosis and stage at presentation for head and neck cancers. In others cancer types there is evidence to support a relation between delay in the diagnosis and disease stage. For example, in patients presenting with Brest cancer, a strong correlation between patient delay and stage at diagnosis has been demonstrated. However, several studies have had conflicting conclusions about relation between diagnostic delay and tumor stage.
In their study Abdoul Hossain Madani et al (2010) describe, the low level of educational status was widespread among cases compared to the controls. The majority of cases was the rural residents and had agriculture as occupation. This is the main source of their monthly income; the cases had relatively lesser income compared to the controls. Their study thus suggests that, the risk of oral cancer is inversely proportional to increasing level of education and economical status. It is further confirmed by multivariate analysis, which shows that education, particularly low level of education, occupation like agriculture and blue collar worker and low monthly household income were the significant independent risk factors.
As Dentists confronted with the diseases of oral cavity, they play an important role in oral cancer prevention by promoting a healthier life style and by performing oral screening for an early diagnosis.
The study is designed to analyze the relationship of patients and tumor related factors with advanced stage of oral squamous cell carcinoma with a goal for better understanding related diagnostic delay which would shed some more light in this matter and would help the clinician for early diagnosis of oral squamous cell carcinoma.
Aims and objectives
General:
· To identify the factors associated to delay in diagnosis of OSCC at advanced stage and way for early diagnosis.
Specific:
· To evaluate the relationship of patient related factors and tumor related factors associated with patients delay and professional delay for diagnosis of OSCC.
· To identify the role of health care professionals in diagnosis of OSCC.
Literature review
Grosky et al (1995) analyzed data for 543 patients with oral or oropharyngeal cancers. The data was obtained from a government cancer registry. Patients were excluded if the data base did not include all the variables under investigation. The data were analyzed using univariate statistical methods. No significant relation between delay and stage was shown and no difference was found between the types of referrer (doctor versus dentist).
Amir et al (1999) studied diagnostic delay in a United Kingdom population. One hundred and eighty eight subjects with head and neck cancer referred to head and neck clinic at a UK hospital were interviewed. No significant association between diagnostic delay and gender, age or tumor size was found.
Kerdapon et al (2001) studied factors relating to the delay in diagnosis of oral squamous cell carcinoma in a population from southern Thailand. One hundred and sixty one patients who presented to the head and neck clinic, the radiotherapy clinic or the dental clinic were the interviewed using a structured interview questionnaire. The resulting data was analyzed using both univariate and multivariate analyses. None of the following variables were found to be significantly related to either professional or patient delay; sex, age marital status, tumor size, lymph node metastasis, occupation, or referrer type (doctor or dentist). Only the use of traditional herbal treatment was associate with a significant relation delay. The authors of this study note that some social, cultural and economic factors peculiar to this area of Thailand may influence the result of this study.
Professional and patient delays in the diagnosis of oral cancer were investigated in a Japanese population by onizawa et al (2003). this study categorized the process of diagnosis oral cancer into four stages; step one was the time from the first awareness of symptoms by a patient to presentation to a healthcare professional, step two was the time from the date of the first consultation to the receipt by the patient of a referral letter, step three was the period from the receipt of the letter by the patient till the first consultation at the tertiary treatment facility and step four was the period from visiting the referral centre till a diagnosis was made. Data was derived from a retrospective chart review which yielded 152 subjects. No relation between delay and gender, past history of cancer, age smoking, alcohol use or incidence of daily medication use was demonstrated. There was no relation between patient delay and T or N stage.
Pitipaht et al (2002) analyzed factors influencing delay in diagnosis of oral and oropharyngeal cancer in a Greek population. A structured interview of 105 consecutive patients referred to one of three teaching hospitals in Athens was undertaken. Patients with a prior history of oral carcinoma were excluded. This study did not analyzed professional delays, and it defined a delay in diagnosis as being present if more than 21 days elapsed from the patient becoming aware of symptoms and presenting to healthcare. This study did show a significant relation between delay in diagnosis and stage IV tumors. Patients who were unmarried and who were ex-smokers were also significantly associated with a delay in diagnosis. This study found no relation between gender, age, educational level or alcohol use.
Jovanovic et al (1992) analyzed 50 consecutive Dutch patients with oral squamous cell cancer who presented to a department of oral and maxillofacial surgery in the Netherland. This study looked at patient delay, professional delay and total delay. Patient delay was defined as the period of time between a patient first noticing a symptom till there presentation to a HCP. Professional delay, which was termed doctor delay in this study, was defined as the time period between the first consultation with a HCP and the final diagnosis. The data was analyzed using unifactoral techniques. No relation between gender, tumor size or site of tumor and delay was found. No difference in professional delay between doctors and dentist was found.
Dimitroulis et al (1992) analyzed 51 consecutive patients presenting to the royal Melbourne Dental Hospital and who were eventually diagnosed with oral squamous cell carcinoma of the mouth. This paper claims that dentist referred significantly more patients with oral squamous cell carcinoma than general medical practitioners and that patient referred by general medical practitioners had higher stage tumors than those referred by dentists. No attempt to justify these claims statistically was made. The patients are more likely to be from lower socioeconomic backgrounds and they are more likely to be referred by dentist than medical practitioners to a dental hospital.
Wildt et al (1995) found that patients with small tumors had more professional delay. One possible explanation is that diagnosis is easier when the tumors are larger because they are visible and cause more complaints.
Li and Guo et al reported that if the reason for the first consultation was a mass in the mouth, the time of patient delay would be extended, where as if the lesion site was gingival; there was an inverse correlation with patient delay.
Amsel et al found patterns of referral were related to “anatomical province” with dentists referring a higher proportion of oral cancers and physicians referring patients with cancers at virtually all other head and neck sites. In addition they found that patients with late stage disease were more likely to be referred from physicians. They suggest that this was because these patient waited until the disease was more serious and then presented to their physician.
Debbie M. Tromp et al (2005) studied three hundred and six patients which were newly diagnosed with carcinoma of the pharynx, larynx, and oral cavity. their result suggest that beyond tumor related factors, the patient’s care seeking behavior contributes to an increased risk of being diagnosed with an advanced tumor of the head and neck.
In a retrospective study, Hollows et al (2000) examined the records of 100 consecutive patients presenting to a department of oral and maxillofacial surgery in a district general hospital in the United Kingdom. Data was analyzed utilizing unifactorial techniques. No correlation between patients delay, T stage, alcohol or cigarette use was found.
Scott et al (2005) studied 245 patients who presented with oral squamous cell carcinoma to a head and neck cancer unit in London,UK. This study excluded patients with a previous diagnosis of cancer anywhere. A standardized structured interview was completed in order to identify factors which may influence the time taken to achieve a diagnostic outcome. No statistically significant association between diagnostic delay and tumor stage could be shown. Being female or married was predictive of presenting with early stage disease. The type of referrer (doctor, dentist, and specialist) was not significantly related to duration of delay.
Schentler et al (1992) compared professional delay in the diagnosis of oral cancer between medical practitioners and dentists. Data was obtained by analyzing the referral letters of patients diagnosed with an intraoral tumor and who were referred to one of three oral and maxillofacial surgery departments in there district hospitals in the UK. Patients were excluded if the referral letters deemed to not include sufficient information. The criteria used to define professional delay were that delay in referral was considered to be present if referral from primary healthcare professional did not occur within two days of initial presentation. No statistical test measuring the significance of relation between variables undertaken, however this study claims that general medical practitioners were better at referring cases of oral cancer than their dental colleagues.
As can be seen from the previous discussion, there is a considerable body of literature pertaining to delays in the diagnosis of head neck cancer.
Chapter: Two
Material and Method
Study design:
A cross sectional study.
Place of study:
Dhaka Dental College and Hospital.
Department of E.N.T Dhaka Medical College and Hospital.
Period of study:
From April 2009 to July 2010.
Sample size:
Total number of patients is 53.
Inclusion criteria:
Patients having stage III and IV tumors on the basis of TNM staging.
Exclusion criteria:
Stage I and II lesion on the basis of TNM staging.
Handicap patients.
Sample selection
The data were collected from Dept. of Oral and Maxillofacial Surgery, Dhaka Dental College and Hospital, and Dept. of ENT, Dhaka Medical College and Hospital. Patients diagnosed with OSCC of the oral cavity at advanced stage were taken. The diagnosis confirmed by histopathology. Informed consent was obtained from all patients, who participated in the study. Patients were all newly diagnosed.
Variables
· Dependent variables.
1. Patient delay.
2. Professional delay.
3. Diagnostic delay (total delay)
· Independent variables
1. Sex.
2. Age.
3. Employment status.
4. Education.
5. Area of residence.
6. Initial symptom.
7. Visibility of tumor.
8. Initial Selection of profession.
9. Cost of transportation from home to local hospital.
10. Cost of transportation from home to specialized/tertiary/oral and maxillofacial surgery unit/head and neck clinic.
Data abstraction
· A self-designed questionnaire is developed (appendix A). Data were collected during interview. Five significant dates were identified for each patient with regards to their diagnostic journey.
· The date that patient first noticed symptoms or signs.
· When the patient first presented to a health care professional.
· When patient first attended the head and neck hospital.
· The date of biopsy taken.
· The date confirmed by histopathology.
If patients could not remember exact date of noticing the onset of symptoms when asked about this, the nearest month was recorded and the date the patient first noticed symptoms was taken to be the first day of that month.
Stage III and IV were defined as advanced stage. A subject is defined as being delayed If 21 or more days had elapsed between first notices of signs or symptoms by the subject and the definitive oral cancer diagnosis. This interval of 3 weeks allows for a seven to ten days follow up of a symptom, then a second visit to referred to a specialized or takes a biopsy and also the time required for a histopathologist to report the result back to the dentist or physician. The length of delay is defined the number of days beyond the 20th day after initial symptoms.
Data collected on socio-demographic status, betel quid chewing, smoking and drinking behavior, previous medical experiences and knowledge of cancer, primary symptoms such as ulcer, pain, pain and ulcer are confirmed.
Area of residence classified as urban and rural. Municipal areas and sanitary districts and thanas are considered urban and others areas rural. Employment status such as employed or unemployed (if a women is not directly involve in any earning work, she is considered as unemployed.) is considered. Income status (as domestic economic condition such as) below 60,000/-(<60,000/-) bdt per year, within 60,000/- 84,000/-(60,000/- to 84,000) bdtaka per year and 84,000/-bdtaka to above (>84,000/-) are considered.
Their education level (illiterate, primary, secondary=from class vi to upper level), visibility of tumor (clear visible=which can be visible just on opening of mouth, moderate visible= needs some effort to see the cancer), initial selection of profession (dentist/Gp/others=chemist, rural or local medical assistant, kobiraj), cost of transportation (home to local hospital and home to any tertiary hospital) are taken as independent variable.
Classification of diagnostic delay
The delay experienced by a patient from noticing a symptom to receiving a diagnosis of head and neck cancer was divided into three components:
1. Patient delay.
2. Professional delay.
3. Total delay.
Patient delay was defined as the time period from a patient first becoming aware of symptoms till their first presentation to a health care professional (HCP).
Professional delay was defined as the time period from their presentation to a HCP to the confirmation by a biopsy.
Total delay was defined as the time period from the first being aware of a symptom to the confirmation of a biopsy (proven diagnosis of oral squamous cell carcinoma.) and it is the diagnostic delay.
Statistical analyses
Descriptive and frequency distribution statistics were generated.
The following continuous outcome measures were assessed:
· Patient delay.
· Professional delay.
· Total delay.
Statistical analysis was carried out using statistical software the SPSS system for windows, version 16.0 (statistical package for social science, Inc, Chicago, IL). For categorical independent variables mean compare independent two tailed “t” test and one way ANOVA (ANOVA) test was performed. The ANOVA tests were followed by post hoc scheffe and tamhane method test. In case of independent continuous variable linear regression and co-relation test was done. In all respective 95% confidence intervals were estimated. All values are expressed as mean ± SD, with significance defined as P<.05.
Chapter: Three
Results
Distribution of age
Figure 01: Bar diagram of age distribution.
The figure illustrates the age distribution of the study. The total number was 53, age ranges from 35 years to 90 years. The mean value was 46.45 years.
Distribution of gender
Figure 2: Pie diagram of gender frequency.
Out of 53 subject, male was 38 (72%) and female was 15 (28%).
Distribution of area of residence.
Figure 3: Pie diagram of area of residence.
Out of 53 subject rural resident number was 37(69.8%) and urban was 16(30.2%).
Distribution of level of education
Figure 4: pie diagram of level of education.
The figure 4 shows level of education of the subject. Out of 53 subject the number of illiterate was 31(59%), primary was 16(30%) and secondary was 6(11%).
Distribution of the initial symptom.
Figure 5: pie diagram of initial symptom.
The figure 5 illustrate pie diagram of initial symptom of the people in this study. Out of total 53 subject, 9(17%) had the pain and ulcer, 22(41%) had the pain only and also 22(41%) had the ulcer symptom.
Distribution of initial selection of profession.
Figure 6: Pie diagram of initial selection of profession.
Total number of subject was 53 among them initial selection of profession for Dentist 11(20.8%), GP 15(28.3%), Others 27(50.9%).
Figure 07: Bar diagram of cost of transportation from home to local hospital.
The figure 07 illustrates diagram of cost of transportation from home to local hospital which ranges from 5 BD taka to 50 BD taka and the mean was 26.32 BD taka.
* cost of transportation from home to local hospital.
Figure 8: Bar diagram of cost of transportation from home to tertiary hospital.
The figure 08 illustrates diagram of cost of transportation from home to tertiary hospital which ranges from 50 BDtaka to 800 BDtaka and mean was 449.43 BDtaka.
* cost of transportation from home to tertiary hospital
Patient’s delay by days
Figure 09: Bar diagram of patients delay and its frequency
The bar diagram shows patients delay and its frequency. The patients delay ranges from 4 days to 30 days and mean 9.92 days.
Figure 10: Bar diagram of professional delay and its frequency.
The figure shows bar diagram of professional delays and its frequency. Out of 53 subjects professional delay ranges from 20 days to 690 days and mean 105.66 days.
Figure 11: Bar diagram of total delay and its frequency.
The figure 11 illustrates total delay and its frequency. The total delay ranges from 30 days to 720 days with mean 115.77 days.
Table 1.1: Association between potential predictor variables and patient delay.
| Variables | Mean (days) | P value | |
| Gender | Male | 9.39 | .294 |
| Female | 11.27 | ||
| Age | .778 | ||
| Employment status | Employed | 8.66 | .046 |
| Unemployed | 11.46 | ||
| Area of residence | Urban | 7.75 | .013 |
| Rural | 10.86 | ||
| Visibility of tumor | Clear visible | 8.93 | .149 |
| Moderate visible | 10.96 | ||
| Transport cost | Cost for local hospital | .911 | |
| Cost for tertiary hospital | .002 |
For categorical variables Independent two tailed “t” test was done and for independent continuous variable linear regression was done.
Here area of residence (P=0.013), employment status (P=0.046) and cost of transportation from home to tertiary hospital were significant (P=0.002). (Significant value set as P<.05).
Table 1.2: Association between income status and patient delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| <60,000 | 26 | 11.42 | <60,000 & 60,000 to 84,000 | .552 |
| 60,000 to 84,000 | 10 | 9.40 | <60,000 & >84,000 | .090 |
| >84,000 | 17 | 7.94 | 60,000 to 84,000 & >84,000 | .763 |
| Total | 53 | 9.92 | ||
The table shows the result of one way ANOVA test. Dependent variable was patient delay. No relation was found.
Table 1.3: Association between level of education and patient delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Illiterate | 31 | 10.84 | Illiterate & Primary | .376 |
| Primary | 16 | 8.62 | Illiterate & Secondary | .635 |
| High school | 6 | 8.67 | Primary & Secondary | 1.000 |
| Total | 53 | 9.92 | ||
The table 1.3 shows the result of one way ANOVA test. Dependent variable was patient delay. No association was found in multiple comparisons.
Table 1.4: Association between initial symptom and patient delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Pain | 22 | 8.45 | Pain and Ulcer | .105 |
| Ulcer | 22 | 11.95 | Pain and pain & Ulcer | .999 |
| Pain &ulcer | 9 | 8.56 | Ulcer and pain & Ulcer | .121 |
| Total | 53 | 9.92 | ||
The table 1.4 shows the result of one way ANOVA test. Dependent variable was patient delay. There was no relation between initial symptom and patient delay.
Table 1.5: Association between initial selection of profession and patient delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Dentist | 11 | 8.27 | Dentist and GP | 1.000 |
| GP | 15 | 8.27 | Dentist and Others | .195 |
| Others | 27 | 11.52 | GP and Others | .134 |
| Total | 53 | 9.92 | ||
The table 1.5 shows the result of one way ANOVA test. Dependent variable was patient delay. The mean patient delay for initial selection of profession was 9.92 days. No comparison was significant.
Table 2.1: Association between potential predictor variables and professional delay
| Variables | Mean (days) | P value | |
| Gender | Male | 92.24 | .172 |
| Female | 139.67 | ||
| Age | Age | .766 | |
| Employment status | Employed | 88.10 | .218 |
| Unemployed | 126.88 | ||
| Area of residence | Urban | 52.19 | .022 |
| Rural | 128.78 | ||
| Visibility of tumor | Clear visible | 81.11 | .117 |
| Moderate visible | 131.15 | ||
| Transport cost | Cost for local hospital | .778 | |
| Cost for tertiary hospital | .001 |
For categorical variables Independent two tailed “t” test and independent continuous variable linear regression and co-relation was done. Here area of residence (P=0.022) and cost of transportation from home to tertiary hospital (P=0.001) were significant with professional delay. (The significant value set as P<.05.)
Table 2.2: Association between income status and professional delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| <60,000 | 26 | 150.19 | <60,000 and 60,000 to 84,000 | .095 |
| 60,000 to 84,000 | 10 | 83.00 | <60,000 and >84,000 | .007 |
| >84,000 | 17 | 50.88 | 60,000 to 84,000 and >84,000 | .002 |
| Total | 53 | 105.66 | ||
One way ANOVA test performed. Dependent variable was professional delay. There is relation with increasing income level. In multiple comparison Income level between <60,000 & >84,000 (P=0.007) and 60,000-84,000 & >84,000 (P=0.002) were statistically significant. The significant level was set as P<.05 and confidence interval was 95%.Table 2.3: Association between education level and professional delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Illiterate | 31 | 118.71 | Illiterate and Primary | .833 |
| Primary | 16 | 97.50 | Illiterate and Secondary | .517 |
| Secondary | 6 | 60.00 | Primary and Secondary | .790 |
| Total | 53 | 105.66 | ||
The table 2.3 shows the result of one way ANOVA test. Dependent variable was professional delay. No comparison found significant.
Table 2.4: Association between initial symptom and professional delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Pain | 22 | 68.55 | Pain and Ulcer | .067 |
| Ulcer | 22 | 154.41 | Pain and Pain & ulcer | .849 |
| Pain and ulcer | 9 | 72.22 | Ulcer and Pain & ulcer | .124 |
| Total | 53 | 105.66 | ||
One way ANOVA test was done. Dependent variable was professional delay. No relation found significant.
Table 2.5: Association between initial selection of profession and professional delay.
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | sig | |||
| Dentist | 11 | 55.00 | Dentist and GP | .902 |
| GP | 15 | 59.33 | Dentist and Others | .006 |
| Others | 27 | 152.04 | GP and Others | .008 |
| Total | 53 | 105.66 | ||
Table 2.5 shows the result of one way ANOVA test. Dependent variable was professional delay. There was association in multiple comparisons between professional delay and initial selection of profession. Others profession shows higher professional delay. The relation between Dentist & Others (P=0.006) and GP & Others (P=0.008) found statistically significant. But no relation found between GP and dentist.
Table 3.1: Association between potential predictor variables and total delay
| Variables | Mean (days) | P value | |
| Gender | Male | 101.89 | .174 |
| Female | 150.93 | ||
| Age | Age | .775 | |
| Employment status | Employed | 97.10 | .224 |
| Unemployed | 138.33 | ||
| Area of residence | Urban | 59.94 | .022 |
| Rural | 139.92 | ||
| Visibility of tumor | Clear visible | 90.41 | .119 |
| Moderate visible | 142.12 | ||
| Transport cost | Cost for local hospital | .787 | |
| Cost for tertiary hospital | .001 |
The table 3.1 illustrates the result of independent two tailed “t” test for categorical variables and linear regression for independent continuous variable. Here area of residence (P=0. 022) and cost of transportation from home to tertiary hospital (P=0. 001) were significant with total delay. The significant level was set as P<.05 with 95% confidence interval.
Table 3.2: Association between income status and total delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| <60,000 | 26 | 162.00 | <60,000 and 60,000 to 84,000 | .095 |
| 60,000 to 84,000 | 10 | 92.40 | <60,000 and >84,000 | .007 |
| >84,000 | 17 | 58.82 | 60,000 to 84,000 and >84,000 | .001 |
| Total | 53 | 115.77 | ||
The table 3.2 shows the result of one way ANOVA test. Dependent variable was total delay. Here multiple comparison between <60,000 & >84,000 (P=0.007) and 60,000-84,000 & >84,000 (P=0.001) were statistically significant with total delay. The significant level was set as P<0.05 and confidence interval 95%.
Table 3.3: Association between education level and total delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Illiterate | 31 | 129.87 | Illiterate and Primary | .809 |
| Primary | 16 | 106.12 | Illiterate and Secondary | .514 |
| Secondary | 6 | 68.67 | Primary and Secondary | .804 |
| Total | 53 | 115.77 | ||
The table 3.3 illustrates the result of one way ANOVA test. Dependent variable was total delay. No association was found with total delay and level of education.
Table 3.4: Association between initial symptom and total delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | Sig | |||
| Pain | 22 | 77.45 | Pain and Ulcer | .068 |
| Ulcer | 22 | 166.36 | Pain and Pain & ulcer | .878 |
| Pain and ulcer | 9 | 85.78 | Ulcer and Pain ulcer | .121 |
| Total | 53 | 115.77 | ||
One way ANOVA test performed. Dependent variable was total delay. Statistically no association was found with total delay and initial symptom.
Table 3.5: Association between initial selection of profession and total delay
| Descriptive statistics | Multiple comparison | |||
| Post hoc | ||||
| n | Mean(days) | |||
| Comparison | sig | |||
| Dentist | 11 | 63.27 | Dentist and GP | .910 |
| GP | 15 | 67.60 | Dentist and Others | .006 |
| Others | 27 | 163.93 | GP and Others | .008 |
| Total | 53 | 115.77 | ||
The table 3.5 illustrates the result of one way ANOVA test. Dependent variable was total delay. The others profession showed significant total delays (mean 115.77days). There was statistical relationship between initial selection of profession and total delay. The significant level was set as P<.05 and confidence interval 95%.
Discussion
Oral squamous cell carcinoma is a vital health problem in Bangladesh. For improving survival rate and reducing morbidity, early detection of the disease is an important factor. This study was conducted in order to investigate the factors responsible for the delay in diagnosis with advanced stage of OSCC. Fifty three patients with oral squamous cell cancer were investigated for delay in diagnosis. The mean duration of patient delay is 9.92 days and varies from 4 days to 30 days. In this study mean professional delay is 105.66 days and ranges from 20 days to 690 days. In case of total delay or diagnostic delay the mean is 115.66 days and varies from 30 days to 720 days.
Twelve variables were examined, among them area of residence, income level and initial selection of profession seems to be statistically significant others are not. All potential predictor variable analyzed will be discussed now.
There is also no relation between age and any type of delay (P value .775 for diagnostic delay). This result is an accord with other studies. But Wildt et al (1995) found that gender and age are associated with patient delay.
There was no significant association between gender and any of the three categories of delay examined. This is an accord with other studies. There is trend to a longer delay seen with mean days for female in this study. Previous studies had shown there was a gender difference when stage of tumor at diagnosis was examined. Scott et al (2005) showed early stage tumors were more likely to be found in women. But in this study, females have longer delay. It may be due to socioeconomic condition of this country which is different from first world country. Here females are financially not independent. They have to depend on the earning member of the family to go for any kind of treatment.
We found statistically significant association in patient delay and employment status (P=0.046) but no relation with professional delay and diagnostic delay. In this study unemployed patients have longer delay. But previous studies found no relation (Onizawa K et al 2003). Employment status considered as a marker of social and economic status but there is no more evidence in the literature to support this proposed link. The rationale for this theory is that patients from socially or economically deprived backgrounds are more likely to have difficulties in accessing health care than patients form more privileged backgrounds. The unemployed people are always dependent on the employed person. More over females patients who performed only home duties were considered as unemployed. As they are depended to others, this play role on delay.
There is significant relationship between area of residence and three types of delay (P=0. .022 for diagnostic delay). Patients in rural area are said to be more delay than those live in urban area. This is because of low social status and low education level and also some local believes. They have also lack of knowledge of cancer and its predisposing factors. Even they think betel nut chewing is helpful for relive from dental and oral ulcer pain. The communication system is one of the factors which play role in delaying diagnosis and treatment. Many of them live in remote area where health facilities are not available. Approaching to a GP or dentist is far beyond. So it is difficult to go very early to doctor for diagnosis and treatment. Another factor, traditionally rural people have the habit of using raw tobacco and betel nut chewing. When they feel sick they first try to resolve it spontaneously and if not occurred then go to local kabiraz or homeopathic doctor. It also causes delay on diagnosis. On the contrary urban people approaches to physician or hospital very easily. But in our study their mean diagnostic (total) delay in days is also very high. This can be explained by their low socioeconomic conditions, which distract them from receiving early diagnosis and treatment. In Bangladesh, there are a very good number of people in urban area who have low income level and have disease prone habit. They cannot afford appropriate health service. And make delay in patient level and also in diagnosis level.
There is statistically significant relationship among low income level and high income level in respect to diagnostic delay. Increasing with income people become more health conscious. And they try to approach regular medical checkup and early treatment. We know that population at risk for oral cancer come from poorest social class. Hence are seen at the public health service in Bangladesh. So lower occupational class was found to be associated with longer diagnostic delay
No statistical association found among level of education and three types of delay. But have greater delay in all level among the illiterate group. The education level is very low among the person who lives in rural area in low socio-economic condition. They have lack of knowledge about oral cancer and its risk factors. More over they have limited opportunity of health service. As a result they appear advanced stage when diagnosis is done.
There is no significant association between visibility of tumor and any three types of delay examined. In this study moderately visible tumor have comparatively longer duration of delay (mean diagnostic/total delay is 142.12 days) but not significant (P=.112). Tumor site may be important in certain areas that are more visible or noticeable than others and tumor at certain sites may have a greater or lesser capacity for rapid growth. Kerdapon D., Sriplung H. (2001) showed tumors at less visible area such as alveolar area, palate, and retro molar area were more likely to be diagnosed at advanced stage compared to easily visible area. He also showed floor of mouth tumors are easy to see directly by patient which may led to earlier consultation to HCPs.
No association was found between initial symptom and any three types of delay. Pain and pain & ulcer have similar type of mean delay. But ulcer has the longer duration in this study. During personal interview they revealed when they have ulcer they showed negligence and taken vitamin b-12 tablet to resolve it. Thus they contribute longer (mean 154.41days) professional delay. Heckett et al found that pain was not a good predictor of reduced delay. Kerdapon D., Sriplung H. (2001) showed patients initially presenting with an ulcer were less likely to be diagnosed with advanced stage disease compared to other symptom (pain, mass). But this study does not support it.
There is association between cost of transportation incase of home to tertiary hospital with delay. But no association was found with home to local hospital. Mean cost of transportation from home to tertiary hospital is 449.43BDtaka. This is very high for low economic class people. It’s very difficult situation for unemployed and female patients.
There is significant association between initial selection of profession and professional delay and total delay, but no association with patient delay. In Bangladesh most of the peoples don’t go to a physician initially and go to a chemist and takes some medicine to resolve the symptom. In rural areas the picture is same but added with quack or polli chikitsok (unqualified medical practitioner) character. When initial symptom appears, people go to unqualified medical practitioner and start treatment. After a long time when they (unqualified medical practitioner) failed to resolve the problem, then people go to hospital or seek a physician. This incident plays a vital role in diagnosing a disease at advanced stage or at complicated stage. During interview with patients they revealed this type of incident. Again patients living in urban area and having well economic status seek physician and hospital from beginning. They have regular medical checkup and they prefer private hospital than to public hospital.
Debbie M. Tromp et al (2005) found no relation delay due to general practitioner or dentist or due to the medical specialist. Wei Gao and Chuan Bin Guo (2009) studied 102 cases of OSCC and found the patients receiving certain treatment (non cancer treatments) before diagnosis had a dramatically increased delay in diagnosis. Grosky M. and dayan D. (1995) found that the consultation with physicians was associated with advanced stage disease. The physician’s role in the diagnosis of OSCC is mandatory since the dentist is mainly confronted with the diagnosis of lesions presented within the boundaries of the oral cavity (the gingiva, floor of the mouth, tongue, palate, buccal mucosa).
Limitation of the study
The small numbers of samples in this study preclude the unmasking of potential predictors of diagnostic delay. Whilst certain trends in the data may be noted, it is not possible to comment any further with any scientific rigor.
The accurate date of initial symptoms could not found. Often patients could not recall an exact onset of symptoms and an estimate of the date of onset needed to be made. There is also lack of proper referral system. Hence we could not include referral delay in this study. As the measurement of patient delay is based on retrospective recall, therefore, subject to recall bias. Biopsy delay and referral was not included in this study.
More variables such as ways of transport system, distance from home to hospital, HHCP’s knowledge of oral cancer was not included.
Conclusion
Current study made an attempt to identify the patient and tumor related factors which are responsible for delay in the diagnosis for oral squamous cell carcinoma. The study hereby concludes that the area of residence, cost of transportation from home to tertiary hospital, employment status, income status and initial selection of profession are the factors responsible for the diagnostic delay of oral squamous cell carcinoma in Bangladesh.
Recommendations
As the OSCC having high morbidity and mortality, it is suggested that widely spread educational campaigns against detrimental factors of oral cancer such as high consumption of tobacco, length of tobacco exposure, early establishment of such habit should conduct through the country.
For early diagnosis of oral squamous cell cancer, cancer screening program should run under primary health complex at regular interval. This will markedly reduce the diagnostic delay.
Most of the people live in rural area and they are more prone to develop OSSC, therefore, rural health system should be developed
General practitioner and dentist should be educated to prevent delayed referral. They should be trained properly for any suspicious lesions and increase their clinical skill or knowledge and ability of recognition on the clinical manifestations of the asymptomatic early lesion to diagnose OSCC.
Government health policy should be modified. In Bangladesh unqualified medical practitioner often creates a simple thing to complicate one. Government should come forward to stop any illegal practice. Simultaneously there should be law concerning drug sell.
We should prevent prolong diagnostic pathways leading up to the first day of therapy. Health professionals should be supplemented by innovative diagnostic strategies.
Proper publicity concerning the OSCC should reach the general people through mass media. The clinician and general people needs to be totally aware about the value of early detection of the disease.
Suggesting further study
A more profound study is expected involving multistage hospital, larger representative sample size and longer study period.
References
· Abdoul Hossain Madani, Abdolreza Sotoodeh Jahromi, Modhurima Dikshit, Debangshu Bhaduri, Teamur Aghamolaie, 2010, Socio-demographic factors related to oral cancer, Journal of Social Sciences, 6 (2), 141-145
· Allison P., Locker D., Feine J.S., 1998, the role of diagnostic delays in the prognosis of oral cancer, a review of the literature, Oral Oncology,34,161-170
· Amir Z, Kawson SYL, Landes D, Feber T, Williams SA, 1999, diagnostic delays in head and neck cancers, European journal of cancer care,8,193-203.
· Arndt V, Stu¨rmer T., Stegmaier C, Ziegler H , Dhom G and Brenner H, 2002, Patient delay and stage of diagnosis among breast cancer patients in germany – a population based study, British Journal of Cancer, 86, 1034 – 1040.
· Aquiline Peter joseph, march 2007, An investigation into patient & professional delays in the diagnosis of head & neck cancer, MS,University of Sydney
· Chandu A, Smith ACH, 2002, Patterns of referral of patients undergoing surgical management for oral cancer, Australian Dental Journal, 47