Programas de cribado para la detección precoz y la prevención del cáncer oral
Resumen
Antecedentes
El cáncer oral es un problema de salud importante a nivel mundial, su incidencia ha aumentado y la consulta inicial en un estadio tardío es frecuente. Los programas de cribado se han introducido para varios cánceres importantes y han probado ser efectivos en la detección precoz. Debido a las tasas altas de morbilidad y mortalidad asociadas con el cáncer oral, es necesario determinar la efectividad de un programa de cribado para esta enfermedad, como una medida dirigida, incidental o poblacional. Hay evidencia de datos basados en modelos de que una exploración visual oral de los individuos con alto riesgo podría ser una estrategia de cribado efectiva respecto a los costos, y el desarrollo y el uso de ayudas adyuvantes y biomarcadores es cada vez más frecuente.
Objetivos
Evaluar la efectividad de los métodos de cribado actuales en la disminución de la mortalidad debida al cáncer oral.
Métodos de búsqueda
Se realizaron búsquedas en las siguientes bases de datos: registro de ensayos del Grupo Cochrane de Salud oral (Cochrane Oral Health Group), (hasta el 22 de julio de 2013), Registro Cochrane central de ensayos controlados (Cochrane Central Register of Controlled Trials, CENTRAL) (The Cochrane Library 2013, número 6), MEDLINE vía Ovid (1946 hasta 22 de julio de 2013), EMBASE vía Ovid (1980 hasta 22 de julio de 2013) y CANCERLIT vía PubMed (1950 hasta 22 de julio de 2013). No hubo restricciones de idioma en la búsqueda de las bases de datos electrónicas.
Criterios de selección
Ensayos controlados aleatorizados (ECA) sobre el cribado del cáncer oral u otros trastornos potencialmente malignos mediante exploración visual, azul de toluidina, imágenes fluorescentes o biopsia por cepillado.
Obtención y análisis de los datos
Dos autores de la revisión analizaron los resultados de las búsquedas según los criterios de inclusión, extrajeron los datos y evaluaron el riesgo de sesgo de forma independiente y por duplicado. Se emplearon las diferencias de medias (DM) y los intervalos de confianza (IC) del 95% para los datos continuos y las razones de riesgos (RR) con IC del 95% para los datos dicotómicos. Se habrían realizado metanálisis mediante un modelo de efectos aleatorios si el número de estudios hubiera excedido un mínimo de tres. Se estableció contacto con los autores de los estudios cuando fue posible y cuando se consideró necesario para obtener la información que faltaba.
Resultados principales
Mediante las búsquedas se identificaron 3239 citas. Solamente un ECA con un seguimiento de 15 años cumplió los criterios de inclusión (n = 13 grupos: 191 873 participantes). No hubo diferencias estadísticamente significativas en las tasas de mortalidad por cáncer oral para el grupo cribado (15,4/100 000 personas‐años) y el grupo control (17,1/100 000 personas‐años), con una RR de 0,88 (IC del 95%: 0,69 a 1,12). Se informó una reducción del 24% en la mortalidad entre el grupo de cribado (30/100 000 personas‐años) y el grupo control (39,0/100 000) para los individuos con alto riesgo fumadores o que consumían alcohol o ambos, y fue estadísticamente significativa (RR 0,76; IC del 95%: 0,60 a 0,97). No se encontraron diferencias estadísticamente significativas en las tasas de incidencia. En los pacientes del grupo de cribado, se encontró una reducción estadísticamente significativa del número de personas diagnosticadas con cáncer oral en estadio III o más avanzado (RR 0,81; IC del 95%: 0,70 a 0,93). No se informaron efectos perjudiciales. El estudio se clasificó como de alto riesgo de sesgo.
Conclusiones de los autores
Hay evidencia de que una exploración visual como parte de un programa de cribado poblacional reduce la tasa de mortalidad por cáncer oral en los individuos con alto riesgo. Además, hay un cambio en el estadio y una mejoría en las tasas de supervivencia en la población general. Sin embargo, existe evidencia limitada a un estudio con alto riesgo de sesgo que no consideró el efecto de la asignación al azar por conglomerados en el análisis. No hubo evidencia a favor del uso de tecnologías adyuvantes como el azul de toluidina, la biopsia por cepillado ni las imágenes por fluorescencia como herramientas de cribado para reducir la mortalidad por cáncer oral. Se recomienda la realización de ECA adicionales para evaluar la eficacia y la relación de costo‐efectividad de una exploración visual como parte de un programa de cribado poblacional en países de ingresos bajos, medios y altos.
PICO
Resumen en términos sencillos
Programas de cribado para la detección precoz y la prevención del cáncer oral
Pregunta de la revisión
Esta revisión, hecha por autores del Grupo Cochrane de Salud oral (Cochrane Oral Health Group), se realizó para investigar la efectividad de los programas de cribado actuales para detectar el cáncer oral en un estadio inicial e investigar si dichos programas pueden ayudar a reducir las muertes debido al cáncer oral.
Antecedentes
El cáncer oral ha aumentado en todo el mundo y en general es el sexto cáncer más frecuente. Las tasas más altas de cáncer oral se producen en las capas más desfavorecidas de la población. Los factores de riesgo importantes en el desarrollo de la enfermedad son el consumo de tabaco y alcohol, la edad, el sexo y la luz solar, aunque también se ha documentado la función de la cándida (que causa candidiosis bucal) y el virus del papiloma humano (que causa verrugas). Las personas que beben demasiado y también fuman tienen 38 veces más riesgo de presentar cáncer oral en comparación con las personas que no lo hacen. Estos factores se consideran especialmente importantes en la aparición de la enfermedad en los jóvenes, un grupo que experimenta un aumento de la incidencia de la enfermedad, en particular, en los países donde la incidencia es elevada.
La variación geográfica en la aparición del cáncer oral en todo el mundo es amplia. Por ejemplo, es el cáncer más frecuente en los hombres de la India, Sri Lanka y Pakistán y constituye el 30% de todos los nuevos casos de cáncer en estos países, mientras que solo el 3% de los nuevos casos de cáncer en el Reino Unido son cáncer oral.
Cuando las personas buscan ayuda médica, generalmente el cáncer oral está en un estadio tardío o avanzado y los efectos de la enfermedad, así como el tratamiento, pueden ser muy debilitantes. Las tasas de mortalidad por cáncer oral y los efectos negativos de la enfermedad son elevados y aumentan en lugar de descender en comparación con otros cánceres como el de mama y el de colon.
Los programas de cribado preventivos para otros cánceres han probado ser efectivos en la detección precoz. Sin embargo, aunque existen ventajas del cribado hay desventajas porque puede producir resultados falsos positivos o falsos negativos. El cribado se puede dirigir a grupos de alto riesgo, puede ser incidental (por ejemplo, cuando los pacientes acuden a los servicios sanitarios por otros motivos) o se puede realizar examinando las estadísticas de la población general.
El objetivo del cribado preventivo para la detección precoz del cáncer oral es cribar a los individuos en busca de enfermedades precancerosas que son lesiones como la leucoplasia. El método de cribado más frecuente es la inspección visual de un médico, pero otras técnicas incluyen el uso de un colorante azul especial, el uso de técnicas de imagen y medir cambios bioquímicos en las células normales.
Características de los estudios
La evidencia en la que se basa esta revisión se actualizó el 22 de julio de 2013. El único estudio incluido se realizó en zonas rurales de la ciudad de Trivandrum, en Kerala (India). El estudio incluyó a 191 873 adultos aparentemente sanos de 35 años de edad o más en 13 grupos, con un promedio de 14 759 participantes en cada uno. El cribado se realizó en siete de estos grupos (96 517 participantes) y seis grupos actuaron como control (95 356 participantes). Los participantes se excluyeron si estaban postrados en cama, si presentaban tuberculosis abierta, otras enfermedades debilitantes o si ya padecían cáncer oral.
Profesionales sanitarios formados en la detección de lesiones orales realizaron el cribado de los participantes y registraron sus antecedentes sociales, que incluyeron el uso de paan (buyo), tabaco, alcohol y suplementos nutricionales.
Resultados clave
La revisión encontró que, en general, no existe evidencia suficiente para decidir si el cribado por inspección visual reduce la tasa de muerte por cáncer oral y no hay evidencia sobre otros métodos de cribado. Sin embargo, hay cierta evidencia de que podría ayudar a reducir las tasas de mortalidad en los pacientes que consumen tabaco y alcohol, aunque el único estudio incluido puede estar afectado por el sesgo.
Calidad de la evidencia
La evidencia presentada es de baja calidad y se limitó a un estudio evaluado como de alto riesgo de sesgo.
Authors' conclusions
Background
Description of the condition
Oral cancer is the sixth most common cancer globally and represents a group of conditions with a range of sites and a varied aetiology. Its annual estimated incidence is approximately 275,000, but unlike many other cancers, its incidence is increasing (Warnakulasuriya 2009). There is a wide geographic variation in the incidence of the disease with two‐thirds of the burden born by low‐income and middle‐income countries from South and South‐East Asia, Latin America and Eastern Europe. However, the incidence continues to rise in the West (IARC 2010) and the age standardised incidence of oral cancer in Western Europe has steadily increased over the past two decades (Boyle 2005). Within the European Union countries, the highest male incidence rates are found in France and Hungary, whilst the lowest rates are found in Greece and Cyprus (IARC 2010). India, Sri Lanka and Pakistan have the highest levels of disease, making it the most common cancer for men in these countries and accounts for up to 30% of all new cases of cancer compared to 3% in the United Kingdom (UK) and 6% in France (Cancer Research UK). The age‐adjusted incidence rate from these countries cancer registries range from 3.4 to 13.8 per 100,000 (Ministry of Health 2005; Warnakulasuriya 2009). The incidence of oral cancer for men in Brazil is second only to France and India with an estimated crude rate of 11 per 100,000. In the UK, the incidence of oral cancer is increasing (Conway 2006; Doobaree 2009) and 6236 cases of oral cancer were diagnosed in 2009 (Cancer Research UK). This represents a doubling of the number of cases seen in 1989 and represents a year on year increase of approximately 2.7% per year (Warnakulasuriya 2009). The incidence of oral cancer is strongly associated with social and economic deprivation (Scully 2009; Conway 2010a), with the highest rates occurring in the most disadvantaged sections of the population. Across Europe, inequalities tend to be observed among men, particularly in the UK and Eastern Europe (Conway 2010b).
Important risk factors in the development of the disease are tobacco, betel quid, alcohol, age, gender and sunlight. More recently, a role for candida and the human papillomavirus (HPV) has been documented (Scully 2009). Epidemiological evidence from US populations indicates a strong association between HPV and oropharyngeal cancers (Cleveland 2011). Incidence of HPV globally is unknown but thought to be rising, but estimates from the United States of America (USA) show a substantial increase of HPV‐positive oropharyngeal cancers, rising by 225% in the period between 1984 and 2004 (Sanders 2011). Increased consumption of alcohol has been implicated in the increasing incidence of the disease in the UK (Hindle 2000) at a time when tobacco use is falling (Ogden 2005), although the precise mechanism remains unclear (Ogden 1998). Heavy drinkers and smokers have 38 times the risk of developing oral cancer compared to abstainers (Blot 1988). This is thought to be due to acetaldehyde, the first metabolite of alcohol, which is classified as a Group 1 carcinogen and is also present in tobacco (Salaspuro 2011). Historically, the risk of developing oral cancer increased with age, however, the age group with the highest incidence (26.8%) in the USA between 2003 and 2007 was between 55 and 64 years of age (SEER 2010). In contrast, many patients from high‐incidence countries are below the age of 40 years of age (Warnakulasuriya 2009).
Of equal concern to the increasing incidence, is the lack of any change in the age‐standardised mortality rates, despite advances in surgical and management techniques. This is unlike the falling rates for cancer of the breast and colon (Cancer Research UK). The five‐year survival rates for oral cancer for most countries is approximately 50% (Warnakulasuriya 2009). These have been estimated at 3 to 4 per 100,000 men and 1.5 to 2.0 per 100,000 for women respectively (Warnakulasuriya 2009). Mortality rates from oral cancer have also increased in certain European countries (La Vecchia 2004). The most important determinant factor in cancer survival is diagnostic delay (Onizawa 2003; McLeod 2005), as over 60% of patients present with stage III and IV disease (Lingen 2008), meaning that their management is complex and multidisciplinary. The stage at diagnosis significantly affects five‐year survival, with survival rates approaching 80% for stage I disease, whilst dropping significantly for stage IV disease (Rusthoven 2010). In addition, the morbidity associated with surgery is high, the rate of second primary tumours is greater than any other type of cancer (3% to 7% per annum) (Day 1992) and is more often the cause of death (Lippman 1989).
Description of the intervention
Prevention strategies are important to meet the World Health Organization's (WHO) resolution to incorporate oral cancer into national cancer control programs (Petersen 2009). Although it is important to continue to clarify the public health message and promote primary prevention, determining the feasibility of a national screening programme is an important step in the prevention of the disease. The National Screening Committee define screening as "a process of identifying apparently healthy people who may be at increased risk of a disease or condition" (NSC 2010). Screening can be undertaken across the whole population, opportunistically, when individuals are attending for some other purpose, or selectively, where high‐risk groups are targeted. Programmes for major cancers, such as breast, cervical and bowel cancer have effectively improved the mortality rates and helped to decrease the incidence of these cancers (Gøtzsche 2006; Hewitson 2007). However, it is important to consider both the harms and benefits of any screening programmes. For example, screening for breast cancer has recently been associated with over‐diagnosis and unnecessary treatment causing further physical and psychological harms (Gøtzsche 2013) and so any future programme should always balance these considerations.
How the intervention might work
Screening is predicated on the idea that malignancy is preceded by clinically evident lesions, which if identified early and removed, can either prevent their malignant transformation or reduce their staging. The majority of oral carcinomas are preceded by visible lesions, known as potentially malignant disorders (PMDs) (Warnakulasuriya 2007; van der Waal 2009) that exhibit oral epithelial dysplasia (Scully 2009). A visual screen is not surgically invasive, is painless and has been found to be socially acceptable. Additional Table 1 highlights the different types of PMDs that were considered by the WHO's Working Party on Oral Cancer and Precancer to be important (Warnakulasuriya 2007). The most common form of PMD is leukoplakia (Napier 2008), which has an estimated global prevalence of 2.6% (95% confidence interval (CI) 1.72% to 2.74%) (Petti 2003). However, the extent and rate of progression of dysplasia in leukoplakia is not uniform and can vary from site to site and within the same lesion (Napier 2008).
| The following were identified as PMDs by the World Health Organization's Working Group on Oral Cancer (Warnakulasuriya 2007).
|
The overall malignant transformation rate for oral leukoplakia is up to 5% (Scully 2009; van der Waal 2009), but the lack of uniformity in the extent and the rate of dysplastic change in PMDs means that predicting malignant transformation is problematic. However, there remains a consensus in the literature that the majority of cancers are preceded by a detectable pre‐clinical phase (Napier 2008).
Although there have been no randomised controlled trials (RCTs) in any developed or low‐prevalence populations (Brocklehurst 2010a), Speight et al demonstrated using a simulated model that an oral examination of high‐risk individuals may be a cost‐effective screening strategy (Speight 2006). A recent diagnostic test accuracy review looking at the accuracy of conventional oral examination as a screening test in primary settings found sensitivity estimates to range from 0.50 (95% CI 0.07 to 0.93) to 0.99 (95% CI 0.97 to 1.00) with specificity estimates 0.98 (95% CI 0.92 to 1.00) to 0.99 (95% CI 0.99 to 0.99) (Walsh 2013). Positive predictive values ranged from 0.31 to 0.86; negative predictive values ranged from 0.96 to 0.99 (Walsh 2013). Other adjunctive and diagnostic aids can be grouped into visual staining (toluidine blue), oral cytology using brush biopsy and a number of light‐based techniques (e.g. ViziLite (Zila Pharmaceuticals, AZ, USA) and VELscope (LED Dental Inc, BC, Canada)) (Brocklehurst 2010a).
Why it is important to do this review
The Cochrane Oral Health Group undertook an extensive prioritisation exercise in 2014 to identify a core portfolio of titles that were the most clinically important ones to maintain on the Cochrane Library (Worthington 2015). Consequently, this review was identified as a priority title by both the oral medicine and public health expert panels (Cochrane OHG priority review portfolio).
The RCT provides the strongest level of evidence on which to base clinical decisions (Clarkson 2003) and so represents a level of rigor that is appropriate for assessing the effectiveness of any intervention or programme. As with other cancers, screening for oral cancer and PMDs has potential advantages and disadvantages (Speight 1992). Screening and treatment may offer the opportunity to reduce the incidence of invasive lesions and also could help in decreasing the mortality rates associated with oral cancer. Speight et al demonstrated that targeting high risk groups could result in a pronounced increase in the Quality Adjusted Life Years saved and any associated stage shifts could produce significant cost savings (Speight 2006). However, screening also has the potential to generate false positives and false negatives (Wilson 1968). Earlier versions of this Cochrane review concluded that there was insufficient evidence to support or refute the use of screening for oral cancer in the general population (Kujan 2003; Kujan 2006; Brocklehurst 2010c). The purpose of this latest update was to determine whether the evidence base had changed.
Objectives
To assess the effectiveness of current screening methods in decreasing oral cancer mortality.
Methods
Criteria for considering studies for this review
Types of studies
Randomised controlled trials (RCTs) of screening programmes for the early detection of oral cancer or potentially malignant disorder (PMD), which report on the associated mortality rates subsequent to the screen.
Types of participants
Participants involved in population, selective (high‐risk) or opportunistic screening programmes were included.
Types of interventions
Any health technology used in a screening programme for the detection of oral cancer or PMD:
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visual screening;
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visual staining using toluidine blue;
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oral cytology using brush biopsies;
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fluorescence imaging and light‐based techniques.
As this was not a diagnostic test accuracy review, the definition of a positive case in each of these categories was not defined; each study was assessed on an individual study‐by‐study basis.
Types of outcome measures
The primary outcome measure for this review was oral cancer mortality.
Other outcomes included were:
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incidence of oral cancer or PMD;
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stage at diagnosis;
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adverse effects (outcomes from false positive or false negative results, if known);
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cost data (where reported).
Search methods for identification of studies
Electronic searches
For the identification of studies included or considered for this review, detailed search strategies were developed for each database searched. These were based on the search strategy developed for MEDLINE (OVID) but revised appropriately for each database (Appendix 1). The search strategies for MEDLINE and CANCERLIT used a combination of controlled vocabulary and free text terms. They were linked with the Cochrane Highly Sensitive Search Strategies (CHSSS) for identifying RCTs in MEDLINE: sensitivity maximising versions (2008 revision) as referenced in Chapter 6.4.11.1 and detailed in boxes 6.4.a and 6.4.c of the Cochrane Handbook forSystematic Reviews of Interventions Version 5.1.0 (updated March 2011) (Higgins 2011). The search of EMBASE was linked to the Cochrane Oral Health Group filter for identifying RCTs.
Databases searched
We searched the following electronic databases.
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The Cochrane Oral Health Group's Trials Register (to 22 July 2013) (Appendix 2).
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CENTRAL (The Cochrane Library 2013, Issue 6) (Appendix 3).
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MEDLINE via OVID (1946 to 22 July 2013) (Appendix 1).
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EMBASE via OVID (1980 to 22 July 2013) (Appendix 4).
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CANCERLIT via PubMed (1950 to 22 July 2013) (Appendix 5).
Searching other resources
The following journals were handsearched for this review to 2010:
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Oral Oncology
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British Dental Journal
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Cancer
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Cancer Research
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Community Dental Health
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Community Dentistry and Oral Epidemiology.
For this update, only handsearching done as part of the Cochrane Worldwide Handsearching Programme and uploaded to CENTRAL was included. See the Cochrane Masterlist of handsearched journals for information on journals and issues searched to date.
Language
There were no non‐English papers that required translation. Had such trials been identified they would have been translated through The Cochrane Collaboration.
Unpublished trials
The bibliographies of included papers and relevant review articles were checked for studies not identified by the search strategies above. The authors of identified and included studies were also contacted to identify unpublished or ongoing trials.
Data collection and analysis
Selection of studies
The titles and abstracts obtained from initial electronic searches were scanned for relevance independently by two of the review authors (Paul Brocklehurst (PRB), Anne‐Marie Glenny (AMG)). Reports from the studies that fulfilled the inclusion criteria were obtained. When there was insufficient data in the study title to determine whether a study fulfilled the inclusion criteria, the full report was obtained and assessed independently by the same review authors. Disagreement was resolved by discussion.
Data extraction and management
All studies meeting the inclusion criteria underwent data extraction and an assessment of risk of bias was made. Studies rejected at this and subsequent stages were recorded in the table of excluded studies. Data from each included study was extracted independently using the tool developed and reported in Kujan 2005. Differences were again resolved by discussion. If a single publication reported two or more separate studies, then each study was extracted separately. If the findings of a single study were spread across two or more publications, then the publications were extracted as one. For each study with more than one control or comparison group for the intervention, the results were extracted for each intervention arm. For each trial the following data were recorded.
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Year of publication, country of origin and source of study funding.
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Details of the participants including demographic characteristics and criteria for inclusion.
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Details on the type of intervention and comparisons.
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Details on the study design.
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Details on the outcomes reported, including method of assessment.
Assessment of risk of bias in included studies
Assessment of risk of bias was conducted by three review authors (PRB, AMG, Lucy O'Malley (LO)) using the Cochrane risk of bias assessment tool. The domains that were assessed for each included study were: sequence generation, allocation concealment, blinding, completeness of outcome data, risk of selective outcome reporting and risk of other potential sources of bias.
A description of the domains was tabulated for each included trial, along with a judgement of the risk of bias in accordance with the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0 (Higgins 2011). A summary assessment of the risk of bias across all the domains for each study was then undertaken (Higgins 2011).
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Low risk of bias ‐ a low risk of bias for all key domains.
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Unclear risk of bias ‐ an unclear risk of bias for one or more key domains.
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High risk of bias ‐ a high risk of bias for one or more key domains.
Measures of treatment effect
For dichotomous outcomes, the estimate of effect was expressed as risk ratios with 95% confidence intervals; for continuous outcomes, mean differences were used with 95% confidence intervals.
Unit of analysis issues
The analysis for cluster randomised trials was undertaken, when feasible, at the same level of randomisation, or at an individual level with the effect of clustering being accounted for.
Assessment of heterogeneity
The significance of any discrepancies in the estimates of the treatment effects from the different trials was assessed by means of Cochran's test for heterogeneity, considered statistically significant at the level of P value < 0.1 (Higgins 2011). The percentage total variation across the included studies was used to quantify heterogeneity and expressed as I2, with a value over 50% representing substantial heterogeneity (Higgins 2011).
Assessment of reporting biases
Publication bias would have also been assessed using funnel plot asymmetry (Higgins 2011).
Data synthesis
Meta‐analyses would have been undertaken if the number of trials had exceeded a minimum of three. Risk ratios would have been combined for dichotomous data, and mean differences for continuous data using a random‐effects model, if data had allowed.
Results
Description of studies
A total of 3239 citations were identified through the MEDLINE searches. The full text of 30 articles were retrieved. Following further screening, 26 of these were excluded with reasons (Characteristics of excluded studies). One of the excluded studies did undertake a community‐based randomised controlled trial to examine the efficacy of toluidine blue in Taiwan (Su 2010). However, the primary aim was to determine whether toluidine blue enhanced the detection rate for potentially malignant disorders (PMD), not mortality rate. Although they did link the examined cohort with the National Cancer Registry to determine five‐year follow‐up, the power calculation was based on the former not the latter. As a result, the study was excluded from this review but included in an accompanying diagnostic test accuracy review (Walsh 2013). Only one study (four reports) met the inclusion criteria (Sankaranarayanan 2000). The principal investigator of the included trial (Dr Sankaranarayanan) was also contacted and no other relevant trials were identified (Figure 1).
Study flow diagram.
The included study (Trivandrum Oral Cancer Screening Study; Sankaranarayanan 2000) was designed to have an 80% power at the 5% significance level to detect a 35% reduction in the cumulative mortality rate of oral cancer in 12 years of enrolment between the intervention and the control groups. The study commenced in October 1995 and three rounds of screening at three‐year intervals were planned for the study. The first round was completed in May 1998 and the second was completed in June 2002. The third round was completed in October 2004. A final round of screening was completed in 2009.
All participants (n = 191,873) were apparently healthy residents aged 35 years or older and lived in 13 rural clusters around Trivandrum City, Kerala, India, The mean number of eligible participants in each cluster was 14,759. These clusters were allocated into an intervention arm (n = 7) and a control arm (n = 6) by a blocked randomisation process. Those residents who were bedridden, suffering from open tuberculosis or other debilitating diseases were excluded alongside those participants who had already been diagnosed with oral cancer prior to entry into the study.
In the intervention arm, non‐medical university graduates were initially trained and were provided with two simple manuals on oral visual examination with colour photographs and descriptions of various oral lesions. Eligible participants were interviewed and information relating to demographic, social and personal habits including the use of paan, tobacco, alcohol and dietary supplements was recorded. Tobacco and alcohol cessation advice was provided as appropriate. Oral visual inspections were performed in daylight with the help of a flashlight. All the intra‐oral sites were carefully examined and palpated and the neck was also palpated to detect enlarged lymph nodes. The findings were recorded as normal, non‐referable lesions and referable lesions.
Participants who had a positive screen were referred for examination by a dentist or physician for confirmation. It is unclear whether these clinicians were also trained in the recognition of oral cancer or PMDs. Oral biopsies were performed in those with clinically confirmed homogeneous leukoplakias, non‐homogeneous leukoplakias, oral submucous fibrosis and oral cancers. Surgical excision was undertaken for leukoplakia wherever possible. All PMDs were reviewed regularly.
In the control arm, participants were visited by a "control health worker" who recorded the same sociodemographic information and measured height, weight, blood pressure and respiratory peak flow measurements. The health workers in the control arm were not trained to undertake a visual oral inspection.
Oral cancer mortality was reported as the main outcome measure.
Of the 96,517 eligible subjects in the intervention arm, 25,144 (26.1%) had one, 22,382 (23.2%) had two, 22,008 (22.8%) had three and 19,288 (20.0%) had four cycles of screening. 49,179 (51.0%) individuals were screened in the first round and 55,993 (58.0%), 64,898 (67.2%) and 43,014 (44.6%) were screened in the second, third and fourth cycles respectively. The participation rate (at least one screen) for this group was 88,822 (92%); males (86%) and females (94%). Of the 95,356 eligible subjects in the control group, 43,992 (46.1%) were screened in the fourth cycle.
Demographic details were not provided for the final (fourth) cycle of screening, but were provided for the first three cycles (Additional Table 2). Across the period of the study (all four cycles), 6.3% (n = 5586) of subjects screened as part of the intervention group had a referable lesion and 59% (n = 3298) of these screen positive subjects complied with referral (Additional Table 3). The control group consisted of 95,356 persons. 46% (n = 43,992) of the control group were screened in the final (fourth) cycle and 2.6% (n = 1163) of these were found to have a referable lesion with 16.3% (n = 189) complying with referral.
| Trivandrum Oral Cancer Screening Study | Screening group | Control group |
|---|---|---|
| Number of interviewed participants | n = 7 clusters (87,829: 91%) | n = 6 clusters (80,086: 84%) |
| Gender | 35,687 male 52,142 female | 31,281 male 48,805 female |
| Income (< 1500 rupees (USD 35) per month) | 42,415 (49%) | 30,849 (40%) |
| Occupation (manual workers) | 68,645 (78%) | 55,811 (71%) |
| Education | 68,263 (78%) | 64,291 (78%) |
| Age (years; mean (SD, range)) | 49 (0.7, 48‐50) | 49 (0.8, 48‐50) |
| No habits | 10,933 male (27%) 39,923 female (73%) | 13,996 male (33%) 42,361 female (79%) |
| Chewing habits | 12,329 male (30%) 14,570 female (27%) | 10,586 male (24.9%) 10,748 female (20%) |
| Smoking habits | 26,133 male (63%) 1610 female (3%) | 23,270 male (56%) 609 female (1%) |
| Drinking habits | 17,738 male (43%) 133 female (0.2%) | 15,472 male (37%) 127 female (0.1%) |
SD = standard deviation.
Note: Data on risk factors not available after 4 cycles (15 years), but authors report that the participants had a similar distribution.
| Screening history | Screening group | Control |
|---|---|---|
| Number recruited | 7 clusters (n = 96,517) | 6 clusters (n = 95,356) |
| Not screened | 7695 | 51,365 |
| Screened once | 25,144 | 43,992 |
| Screened twice | 22,382 | |
| Screened three times | 22,008 | |
| Screened four times | 19,288 | |
| Number of screen positive individuals | 5586 | 1163 |
| Individuals complied with referral | 3298 | 189 |
Risk of bias in included studies
Allocation
Sequence generation
The randomisation procedure was conducted using restricted block randomisation. The exact detail of this process was not provided, although the clusters were grouped into blocks of four and allocated at random to screening or non‐screening groups from the six possible combinations available to each block of four. Clustering was not accounted for in the analysis.
Allocation concealment
No detail of allocation concealment was provided, although the principal investigator confirmed that this was not undertaken.
Blinding
Blinding of outcome assessment
No blinding was undertaken in the study, but the review authors judge that the outcome and its measurement are unlikely to be influenced by this. As a result, the risk of bias based on the lack of blinding is considered to be low.
Incomplete outcome data
Withdrawals and drop‐outs were not described clearly and missing data will have increased the risk of bias. Of those who were referred with positive lesions, 59% of individuals in the screening group complied with referral and 16% in the control group (Additional Table 3). The analysis was carried out on an intention‐to‐treat (ITT) basis.
Selective reporting
The study protocol was not made available, but it appears that the published reports include all the expected and pre‐specified outcome measures.
Other potential sources of bias
Positive cases were referred to dentists and physicians to make a diagnosis, but it is unclear whether standardised criteria were used by these clinicians or whether they had received any formal training. It is stated that subjects with confirmed oral cancer and PMDs were biopsied and those with confirmed oral cancer were referred. However, this detail was absent and only 26.4% and 26.0% of subjects with a PMD had a biopsy in the second or third cycle respectively. It is not clear whether all suspected oral cancer cases did receive a biopsy, but given the definition of "interval cases" in the third paper, it would appear not.
In addition, it is stated in the third paper that the reference investigation for final diagnosis was clinical examination by physicians or histology or both. As it is not possible to diagnose early malignancy by visual appearance alone, this may have led to substantial under‐reporting of oral cancer. The lack of a histological diagnosis for many of the PMDs also makes it difficult to accurately assess the correct diagnosis and true prevalence of these disorders. Prevalence of PMDs is provided in detail for the first two cycles only. The fourth paper presents incidence and mortality data for each round of screening. Neither the third or fourth papers present data regarding prevalence of PMDs.
In the included study the health workers reported on 24 baseline variables including multiple age strata, occupation, education, income, household belongings such as television and personal habits of chewing, smoking, and drinking. The intervention and control cohorts appear to have been well matched for the stratified variable age at the baseline. However, the distribution of income, education, use of tobacco and alcohol varied across the intervention and control groups, with the former demonstrating higher levels of consumption (Additional Table 2). Men smoked and drank alcohol more than females in both groups, but the prevalence of chewing tobacco was not as marked across gender differences. Although, such differences in baseline variables might be expected to occur in cluster randomised studies, the differences between the numbers who used tobacco and alcohol need to be borne in mind when interpreting the results.
Effects of interventions
The included study reported data on oral cancer incidence, disease‐specific mortality, and stage at diagnosis after 15‐years follow‐up. Data on quality of life and all cause mortality were not reported.
Oral cancer mortality
There was a 12% reduction in oral cancer mortality between the intervention and control arms, but this difference was not statistically significant. Over the four cycles (15 years), 138 of 279 subjects with oral cancer in the intervention group and 154 of the 244 cases in the control group died, which represents a mortality rate of 15.4 and 17.1 per 100,000 person‐years respectively (risk ratio (RR) 0.88; 95% confidence interval (CI) 0.69 to 1.12). Age‐adjusted rates were 18.9 per 100,000 person‐years in the intervention group and 19.7 per 100,000 person‐years in the control (Additional Table 4).
| Trivandrum Oral Cancer Screening Study | Screening group | Control group | Risk ratio (95% confidence interval) |
|---|---|---|---|
| Total number participants | 96,517 | 95,356 | |
| Person‐years of observation | 895,310 | 898,280 | |
| Number of oral cancers | 279 | 244 | |
| Screen detected cases | 188 | Nil | |
| Deaths from oral cancer | 138 | 154 | |
| Case fatality rate | 49.5% | 63.1% | |
| Crude incidence rate / 100,000 person‐years of observation | 31.2 | 27.2 | 1.14 (0.91 to 1.44) |
| Age‐standardised incidence rate / 100,000 person‐years | 37.1 | 30.8 | |
| Crude mortality rate from oral cancer /100,000 person‐years of observation | 15.4 | 17.1 | 0.88 (0.69 to 1.12) |
| Age‐standardised mortality rate / 100,000 person‐years | 18.9 | 19.7 | |
| Proportion of cancers at stage III or worse1 | 52.6% | 65.2% | 0.81 (0.70 to 0.93) |
1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group).
There was a 24% reduction in oral cancer mortality between the intervention and control arms for those participants who used tobacco or alcohol or both and this difference was statistically significant. Over the four cycles (15 years), 129 of 254 subjects with oral cancer in the intervention group and 147 of the 232 cases in the control group died, which represents a mortality rate of 30.0 and 39.0 per 100,000 person‐years respectively (RR 0.76; 95% CI 0.60 to 0.97) (Additional Table 5). Age‐adjusted rates were 29.1 per 100,000 person‐years in the intervention group and 37.1 per 100,000 person‐years in the control (Additional Table 4).
| Trivandrum Oral Cancer Screening Study | Screening group | Control group | Risk ratio (95% confidence interval) |
|---|---|---|---|
| Person‐years of observation | 429,620 | 377,350 | |
| Number of oral cancer cases | 254 | 232 | |
| Deaths from oral cancer | 129 | 147 | |
| Case fatality rate | 50.8% | 63.4% | |
| Crude incidence rate/ 100,000 person‐years | 59.2 | 61.6 | 0.97 (0.79 to 1.19) |
| Age‐standardised incidence rate/ 100,000 person‐years | 57.3 | 58.5 | |
| Crude mortality rate/ 100,000 person‐years | 30.0 | 39.0 | 0.76 (0.60 to 0.97) |
| Age‐standardised mortality rate/ 100,000 person‐years | 29.1 | 37.1 | |
| Age‐standardised mortality rate/ 100,000 person‐years | 18.9 | 19.7 | |
| Proportion of cancers at stage III or worse1 | 54.3% | 66.4% | 0.82 (0.71 to 0.95) |
1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group).
Although data presented after four cycles (15 years) were not divided by gender, the three‐year cycle data (nine years) showed a significant reduction of 43% in mortality rates for men from 42.9 per 100,000 person‐years in the control group to 24.6 per 100,000 person‐years in the intervention group. For women, there was a 22% reduction, from 50.7 to 39.4 per 100,000 person‐years, but this did not reach significance.
For the participants that adhered to all four cycles of the screening programme, there was a 79% reduction in oral cancer mortality (81% amongst the users of tobacco or alcohol or both) compared to the control, which was statistically significant (Additional Table 6).
| Risk type | Arm | Cycles | Mortality rate* | Hazard ratio (95% confidence interval)** |
|---|---|---|---|---|
| All participants | Control | n/a | 17.1 | 1.00 |
| Screening group | 0 | 37.2 | 1.46 (0.78 to 2.73) | |
| 1 | 44.1 | 2.26 (1.66 to 3.09) | ||
| 2 | 16.2 | 0.94 (0.68 to 1.30) | ||
| 3 | 10.4 | 0.62 (0.37 to 1.04) | ||
| 4 | 3.0 | 0.21 (0.13 to 0.35) | ||
| High‐risk participants | Control | n/a | 39.0 | 1.00 |
| Screening group | 0 | 59.4 | 1.27 (0.68 to 2.37) | |
| 1 | 74.7 | 1.90 (1.45 to 2.49) | ||
| 2 | 31.0 | 0.83 (0.62 to 1.12) | ||
| 3 | 20.6 | 0.53 (0.34 to 0.84) | ||
| 4 | 7.1 | 0.19 (0.11 to 0.31) |
*Per 100,000 person‐years of observation
**Adjusted for age, sex and number of residents.
Oral cancer incidence
Among the 96,517 participants screened in the intervention group, 5586 (6.3%) were found to have referable lesions. Of these, 3298 (59%) complied with the referral criteria for confirmatory examination by dentists or medical officers in special clinics. Healthy mucosa or benign lesions were found in 770 (23.3%). The number of PMDs was 2336 (70.8%) (lichen planus (n = 53), homogenous leukoplakia (n = 898) and submucous fibrosis (n = 573)) and growths suspicious of oral cancer 192/3298 (4%). Of those diagnosed with PMDs, 21.4% (n = 499), underwent biopsies and 4.4% (n = 22) were confirmed squamous cell carcinoma. Of those diagnosed with suspicious growths, 84.9% (n = 163) were confirmed as squamous cell carcinoma and 1.6% (n = 3) as verrucous carcinoma.
The detection rate of PMD and oral cancer in the first, second, and third and fourth rounds of screening were 28.0, 11.9, 11.6 and 3.9 per 1000 screened subjects respectively. The crude incident rate of oral cancer was 31.2 per 100,000 person‐years in the screening group and 27.2 per 100,000 person‐years in the control group, with a risk ratio of 1.14 (95% CI 0.91 to 1.44). Age‐adjusted incidence rates were 37.1 per 100,000 person‐years and 30.8 per 100,000 person‐years respectively (Additional Table 4).
Test performance
Across the four cycles (15 years) of the programme, the reported sensitivity of the visual examination in detecting oral cancer was 67.4% (188/279) (Additional Table 4). No information on the specificity or the positive predictive value of the programme was recorded.
Survival
Survival rates were calculated by comparing the proportion of patients alive at five years after diagnosis across the two groups. A significantly higher five‐year survival rate was reported in the screened group (55.5%) compared to the control (43.4%) (P value = 0.003).
Stage shift at diagnosis
There was a statistically significant stage shift in the cancers that were diagnosed in the screened group, based on the criteria of the International Union Against Cancer/American Joint Committee on Cancer (UICC/AJCC). In the screened group, 147/279 (52.6%) cases were in stage III or worse at diagnosis, as opposed to 159/244 (65.2%) of cases in the control group (RR 0.81; 95% CI 0.70 to 0.93) (Additional Table 4; Additional Table 7). For users of tobacco, alcohol or both, 138/254 (54.3%) cases were in stage III or worse at diagnosis in the screened group, as opposed to 154/232 (66.4%) of cases in the control group (RR 0.82; 95% CI 0.71 to 0.95) (Additional Table 5; Additional Table 7).
| Arm | Cycles | Clinical stage | Total | ||||
|---|---|---|---|---|---|---|---|
| I | II | III | IV | Unknown | |||
| Intervention group | Baseline | 0 | 3 (16%) | 3 (16%) | 7 (37%) | 6 (32%) | 19 |
| 1 | 9 (11%) | 10 (13%) | 18 (23%) | 32 (41%) | 10 (13%) | 79 | |
| 2 | 10 (15%) | 11 (17%) | 17 (26%) | 25 (38%) | 3 (5%) | 66 | |
| 3 | 23 (32%) | 12 (17%) | 9 (13%) | 25 (35%) | 3 (4%) | 72 | |
| 4 | 17 (40%) | 15 (35%) | 4 (9%) | 7 (34%) | 0 | 43 | |
| Total | 59 (21%) | 51 (18%) | 51 (18%) | 96 (34%) | 22 (8%) | 279 | |
| Control group | 1996 ‐ 2004 (detected not due to screening) | 21 (13%) | 19 (12%) | 34 (22%) | 72 (46%) | 12 (8%) | 158 |
| Not screened | 0 | 7 (16%) | 12 (27%) | 20 (44%) | 6 (13%) | 45 | |
| Screened | 10 (24%) | 9 (22%) | 6 (15%) | 15 (37%) | 1 (2%) | 41 | |
| Total | 31 (13%) | 35 (14%) | 52 (21%) | 107 (44%) | 19 (8%) | 244 | |
Cost‐effectiveness
The costs associated with the screening programme were reported after three cycles (nine years) (Subramanian 2009) (Additional Table 8). The benefit produced by a screen was 269.31 life‐years saved per 100,000 for all the individuals and 1437.64 for those at high risk. The incremental cost per life‐year saved was USD 835 for all individuals, which reduced to USD 156 for high‐risk individuals. This fulfils the target set by the World Health Organization (WHO) Commission on Macroeconomics and Health (WHO 2001), who define an intervention to be cost‐effective when its cost‐effectiveness ratio is less than a country's gross domestic product per capita. Subramanian argues that this provides good evidence that opportunistic screening of high‐risk groups is cost‐effective (Subramanian 2009).
| Detail | Cost of intervention less cost of control (US$) | |
|---|---|---|
| Total cost per 100,000 individuals | 224,964 | |
| Cost per additional cancer detected by the screen | All individuals | 4817 |
| Cost per additional cancer detected by the screen | High‐risk individuals | 9394 |
| Cost per life‐year saved by the screen | All individuals | 835 |
| Cost per life‐year saved by the screen | High‐risk individuals | 156 |
Costs based on the calender year of 2004 (Subramanian 2009).
Discussion
The incidence of oral cancer is increasing in low, middle and high‐income countries (Warnakulasuriya 2009). Delays in diagnosis and management persist (Onizawa 2003McLeod 2005) and are associated with a dramatic deterioration in five‐year survival rates. Effective primary and secondary prevention strategies are critical in delivering the World Health Organization's (WHO) resolution that oral cancer should be an integral part of national cancer control programmes (Petersen 2009).
Given that the majority of oral carcinomas are preceded by visible lesions (Scully 2009), determining the efficacy and effectiveness of screening warrants attention, whilst balancing the potential benefits with any potential negative consequences of any programme (Wilson 1968).
Summary of main results
The study reported a sensitivity of the visual examination in detecting oral cancer was 67.4%. However, the data for users of tobacco, alcohol or both demonstrated a reduction in mortality rates of 24% after four cycles (15 years), which was statistically significant. In addition, there was a statistically significant difference in the number of stage III cancers between the intervention and control arms, suggesting that the screening programme was identifying cancers at an early stage. When these results are combined with the significant stage shift and survival rate in the intervention group, it would appear that visual examination could be effective at reducing mortality rates for oral cancer when used within a targeted screening programme. However, the included study had a high risk of bias.
Overall completeness and applicability of evidence
The purpose of health care is to improve both the quantity and quality of life (Kaplan 2005). The evidence from the Kerala trial (Sankaranarayanan 2000) is that visual screening can reduce the mortality rate in users of tobacco, alcohol or both and can produce a stage shift. Given that late stage disease is recognised as a major contributory factor for cancer survival (Onizawa 2003; McLeod 2005), it would appear that the screening of high‐risk individuals could be warranted. However, the evidence from this study stems from a population with a high incidence of oral cavity cancer, and its applicability to other countries with lower incidence rates is unknown. In addition, the efficacy of the early management of potentially malignant disorders (PMDs) is a controversial area (Holmstrup 2007; Holmstrup 2009). Holmstrup argues that even if early lesions are surgically removed, the risk of malignant change can remain as a result of "field change" i.e. the lesion represents only a small area of a wider field of damaged mucosa (Holmstrup 2007; Holmstrup 2009).
The trial used non‐medical university graduates, trained specifically to perform visual inspection of the oral mucosa, with the help of a flashlight. The screening was undertaken in individuals own home, with the health workers going 'door‐to‐door'. The ability to translate this screening model to other settings is unclear. However, the Kerala study does demonstrate the potential of allied health professionals to screen for oral cancer and PMDs. This is becoming increasingly relevant as more regulators allow patients to directly access allied providers of dental care (oral health practitioners), in addition to the dentist.
The cost‐effectiveness of the Kerala study was reported after three cycles (nine years) (Subramanian 2009), demonstrating that 1437.64 life‐years could be saved per 100,000 high‐risk individuals, with an incremental cost per life‐year saved of USD 156. According to the authors, this fulfils the target set by the WHO Commission on Macroeconomics and Health, who define an intervention as being cost‐effective when its cost‐effectiveness ratio is less than a country's gross domestic product per capita. However, these results also need to be read in context of the relative prevalence of the condition and account for the potential problem of compliance; out of the 5586 participants that were screened positive, only 59% (n = 3298) complied with referral.
The consideration of both the benefits and harms of screening is an essential component of any programme (Wilson 1968) and is fundamental to the satisfactory introduction of any technology into daily practice (Duffy 2001). The sensitivity reported in the Kerala study was relatively low (67%). In addition, false positives can have unintended psychological consequences, for example, increasing anxiety and exposing the patient to unnecessary further investigations. However, these could be reduced by careful patient management and by educating screened patients about the positive benefits of screening (Speight 1992). Recent studies by Brocklehurst, highlighted the need to train general dental practitioners to discuss positive findings (Brocklehurst 2010b) and the need for standardised criteria to avoid both under and over‐referral in clinical practice (Brocklehurst 2010).
Quality of the evidence
The Kerala study had a number of methodological weaknesses that may have introduced bias. These included a lack of detail about the process of sequence generation to ensure random assignment, no analysis of the impact of clustering on the results and no detail about allocation concealment. In addition, there was no blinding of the outcome assessment and withdrawals and drop‐outs were not described. More importantly, only 59% of individuals with screen‐positive lesions in the intervention arm complied with referral and it was unclear whether the clinicians who saw these patients followed any standardised criteria. In addition, only 26.4%, 26.0%, and 21.4% of subjects had a biopsy in the second, third cycle or fourth cycle respectively, with no detail being provided from the first cycle. As it is not possible to diagnose early malignancy by visual appearance alone, this may have led to substantial under‐reporting of oral cancer and the lack of a histological diagnosis makes it difficult to accurately assess the correct diagnosis and true prevalence of these disorders. It has been argued that the small number of randomised clusters could also produce statistical heterogeneity and the close geographical proximity of the clusters may have led to contamination (Kujan 2005).
Potential biases in the review process
We conducted a broad search of several databases and placed no restrictions on the language of publication when searching the electronic databases or reviewing reference lists of included studies. All data extraction and risk of bias assessment was conducted in duplicate.
Agreements and disagreements with other studies or reviews
A meta‐analysis of visual screening found a weighted and pooled sensitivity of 84.8% (95% confidence interval (CI) 73.0 to 91.9) and specificity of 96.5% (95% CI 93.0 to 98.2) (Downer 2004). However, there was considerable heterogeneity in the studies pooled due to differences in the size of the target populations and it is arguable that a meta‐analysis was inappropriate. A more recent review has evaluated the diagnostic accuracy of non‐specialist conventional oral examination, vital rinsing, light‐based detection, biomarkers and mouth self examination for the identification of individuals with suspected oral squamous cell carcinoma or PMD. Sensitivity values for studies for all tests were varied and relatively imprecise with sensitivity values ranging from 0.59 (0.39 to 0.78) to 0.99 (95% CI 0.97 to 1.00) for the conventional oral examination (Walsh 2013).
These values of sensitivity and specificity for visual examination have not been surpassed by any other type of method, such as self examination, vital staining (toluidine blue), oral cytology or light‐based techniques (Lingen 2008; Patton 2008; Walsh 2013). The review by Walsh et al showed sensitivity values ranging from 0.18 (95% CI 0.13 to 0.24) to 0.33 (95% CI 0.10 to 0.65) for mouth self examination and a sensitivity value of 0.20 (95% 0.01 to 0.72) for the addition of toluidine blue (Walsh 2013). In Patton's systematic review, 23 studies met the inclusion criteria, yet there remained insufficient evidence to support or refute the use of adjunctive techniques to the visual examination (Patton 2008). In another review, Lingen found that the majority of the published studies had employed these techniques on patients who had already received a diagnosis and that they did not improve upon the sensitivity or specificity of the visual examination (Lingen 2008).
Study flow diagram.
| The following were identified as PMDs by the World Health Organization's Working Group on Oral Cancer (Warnakulasuriya 2007).
|
| Trivandrum Oral Cancer Screening Study | Screening group | Control group |
|---|---|---|
| Number of interviewed participants | n = 7 clusters (87,829: 91%) | n = 6 clusters (80,086: 84%) |
| Gender | 35,687 male 52,142 female | 31,281 male 48,805 female |
| Income (< 1500 rupees (USD 35) per month) | 42,415 (49%) | 30,849 (40%) |
| Occupation (manual workers) | 68,645 (78%) | 55,811 (71%) |
| Education | 68,263 (78%) | 64,291 (78%) |
| Age (years; mean (SD, range)) | 49 (0.7, 48‐50) | 49 (0.8, 48‐50) |
| No habits | 10,933 male (27%) 39,923 female (73%) | 13,996 male (33%) 42,361 female (79%) |
| Chewing habits | 12,329 male (30%) 14,570 female (27%) | 10,586 male (24.9%) 10,748 female (20%) |
| Smoking habits | 26,133 male (63%) 1610 female (3%) | 23,270 male (56%) 609 female (1%) |
| Drinking habits | 17,738 male (43%) 133 female (0.2%) | 15,472 male (37%) 127 female (0.1%) |
| SD = standard deviation. | ||
| Screening history | Screening group | Control |
|---|---|---|
| Number recruited | 7 clusters (n = 96,517) | 6 clusters (n = 95,356) |
| Not screened | 7695 | 51,365 |
| Screened once | 25,144 | 43,992 |
| Screened twice | 22,382 | |
| Screened three times | 22,008 | |
| Screened four times | 19,288 | |
| Number of screen positive individuals | 5586 | 1163 |
| Individuals complied with referral | 3298 | 189 |
| Trivandrum Oral Cancer Screening Study | Screening group | Control group | Risk ratio (95% confidence interval) |
|---|---|---|---|
| Total number participants | 96,517 | 95,356 | |
| Person‐years of observation | 895,310 | 898,280 | |
| Number of oral cancers | 279 | 244 | |
| Screen detected cases | 188 | Nil | |
| Deaths from oral cancer | 138 | 154 | |
| Case fatality rate | 49.5% | 63.1% | |
| Crude incidence rate / 100,000 person‐years of observation | 31.2 | 27.2 | 1.14 (0.91 to 1.44) |
| Age‐standardised incidence rate / 100,000 person‐years | 37.1 | 30.8 | |
| Crude mortality rate from oral cancer /100,000 person‐years of observation | 15.4 | 17.1 | 0.88 (0.69 to 1.12) |
| Age‐standardised mortality rate / 100,000 person‐years | 18.9 | 19.7 | |
| Proportion of cancers at stage III or worse1 | 52.6% | 65.2% | 0.81 (0.70 to 0.93) |
| 1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group). | |||
| Trivandrum Oral Cancer Screening Study | Screening group | Control group | Risk ratio (95% confidence interval) |
|---|---|---|---|
| Person‐years of observation | 429,620 | 377,350 | |
| Number of oral cancer cases | 254 | 232 | |
| Deaths from oral cancer | 129 | 147 | |
| Case fatality rate | 50.8% | 63.4% | |
| Crude incidence rate/ 100,000 person‐years | 59.2 | 61.6 | 0.97 (0.79 to 1.19) |
| Age‐standardised incidence rate/ 100,000 person‐years | 57.3 | 58.5 | |
| Crude mortality rate/ 100,000 person‐years | 30.0 | 39.0 | 0.76 (0.60 to 0.97) |
| Age‐standardised mortality rate/ 100,000 person‐years | 29.1 | 37.1 | |
| Age‐standardised mortality rate/ 100,000 person‐years | 18.9 | 19.7 | |
| Proportion of cancers at stage III or worse1 | 54.3% | 66.4% | 0.82 (0.71 to 0.95) |
| 1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group). | |||
| Risk type | Arm | Cycles | Mortality rate* | Hazard ratio (95% confidence interval)** |
|---|---|---|---|---|
| All participants | Control | n/a | 17.1 | 1.00 |
| Screening group | 0 | 37.2 | 1.46 (0.78 to 2.73) | |
| 1 | 44.1 | 2.26 (1.66 to 3.09) | ||
| 2 | 16.2 | 0.94 (0.68 to 1.30) | ||
| 3 | 10.4 | 0.62 (0.37 to 1.04) | ||
| 4 | 3.0 | 0.21 (0.13 to 0.35) | ||
| High‐risk participants | Control | n/a | 39.0 | 1.00 |
| Screening group | 0 | 59.4 | 1.27 (0.68 to 2.37) | |
| 1 | 74.7 | 1.90 (1.45 to 2.49) | ||
| 2 | 31.0 | 0.83 (0.62 to 1.12) | ||
| 3 | 20.6 | 0.53 (0.34 to 0.84) | ||
| 4 | 7.1 | 0.19 (0.11 to 0.31) | ||
| *Per 100,000 person‐years of observation **Adjusted for age, sex and number of residents. | ||||
| Arm | Cycles | Clinical stage | Total | ||||
|---|---|---|---|---|---|---|---|
| I | II | III | IV | Unknown | |||
| Intervention group | Baseline | 0 | 3 (16%) | 3 (16%) | 7 (37%) | 6 (32%) | 19 |
| 1 | 9 (11%) | 10 (13%) | 18 (23%) | 32 (41%) | 10 (13%) | 79 | |
| 2 | 10 (15%) | 11 (17%) | 17 (26%) | 25 (38%) | 3 (5%) | 66 | |
| 3 | 23 (32%) | 12 (17%) | 9 (13%) | 25 (35%) | 3 (4%) | 72 | |
| 4 | 17 (40%) | 15 (35%) | 4 (9%) | 7 (34%) | 0 | 43 | |
| Total | 59 (21%) | 51 (18%) | 51 (18%) | 96 (34%) | 22 (8%) | 279 | |
| Control group | 1996 ‐ 2004 (detected not due to screening) | 21 (13%) | 19 (12%) | 34 (22%) | 72 (46%) | 12 (8%) | 158 |
| Not screened | 0 | 7 (16%) | 12 (27%) | 20 (44%) | 6 (13%) | 45 | |
| Screened | 10 (24%) | 9 (22%) | 6 (15%) | 15 (37%) | 1 (2%) | 41 | |
| Total | 31 (13%) | 35 (14%) | 52 (21%) | 107 (44%) | 19 (8%) | 244 | |
| Detail | Cost of intervention less cost of control (US$) | |
|---|---|---|
| Total cost per 100,000 individuals | 224,964 | |
| Cost per additional cancer detected by the screen | All individuals | 4817 |
| Cost per additional cancer detected by the screen | High‐risk individuals | 9394 |
| Cost per life‐year saved by the screen | All individuals | 835 |
| Cost per life‐year saved by the screen | High‐risk individuals | 156 |
| Costs based on the calender year of 2004 (Subramanian 2009). | ||
