Background <p>Oral cancer screening can potentially improve the prevention and early detection of tumors if targeted toward at-risk individuals in the population. This study aims to profile the risk factors of oral cancer in a large Nigerian cohort to enable the selection of participants for cancer screening.</p> Methods <p>This multicenter cross-sectional study involved an organized community oral cancer screening conducted among Nigerians between April 2023 and February 2024. Visual oral examination was conducted by trained personnel to determine the presence of oral cancer and precancerous lesions among participants. Additionally, we interviewed all screened participants based on thirty risk factor information items. Multivariate analysis was performed to determine factors that are significantly associated with oral cancer and precancerous conditions, which were used to construct a multivariate predictive model for oral cancer risk stratification.</p> Results <p>Screening of 4049 participants detected 127 cases of oral cancer and precancerous lesions. Eight factors that are significantly associated with having a suspicious oral mucosal lesion at screening include tobacco smoking and snuff use, alcohol drinking, lack of fruits/vegetables consumption, and red/processed meat consumption, low spice consumption level, and comorbidities (p-value: &lt;0.001–0.046). The predictive model based on the significant factors has an AUC of 0.74 (0.72 – 0.76) and Youden’s index of 0.27 (0.25-0.29) that is higher than the metrics obtained for the conventional method of risk profiling for oral cancer (Youden’s index: 0.25 (0.23-0.27)).</p> Conclusions <p>Risk prediction model has better discrimination and net benefit than the conventional approach for identifying at-risk individuals for oral cancer. This finding supports the potential application of this method for risk stratification during targeted oral cancer screening.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Development and validation of a multivariable model to identify candidates for oral cancer screening in Nigeria

  • John Adeoye,
  • Seidu A. Bello,
  • Abdulwarith Akinshipo,
  • Fadekemi O. Oginni,
  • Bukola F. Adeyemi,
  • Ramat O. Braimah,
  • Ibrahim K. Suleiman,
  • Mujtaba Bala,
  • Hector O. Olasoji,
  • Tosin Bakare,
  • Taiwo Ajisebutu,
  • Martina O. Mejabi,
  • Emeka D. Odai,
  • Ekosuehi T. Agho,
  • Ifeoluwa Oketade,
  • Victor I. Orji,
  • Francis J. Bello,
  • Nathan U. Ikimi,
  • Deborah J. Enebong,
  • Yu-Xiong Su

摘要

Background

Oral cancer screening can potentially improve the prevention and early detection of tumors if targeted toward at-risk individuals in the population. This study aims to profile the risk factors of oral cancer in a large Nigerian cohort to enable the selection of participants for cancer screening.

Methods

This multicenter cross-sectional study involved an organized community oral cancer screening conducted among Nigerians between April 2023 and February 2024. Visual oral examination was conducted by trained personnel to determine the presence of oral cancer and precancerous lesions among participants. Additionally, we interviewed all screened participants based on thirty risk factor information items. Multivariate analysis was performed to determine factors that are significantly associated with oral cancer and precancerous conditions, which were used to construct a multivariate predictive model for oral cancer risk stratification.

Results

Screening of 4049 participants detected 127 cases of oral cancer and precancerous lesions. Eight factors that are significantly associated with having a suspicious oral mucosal lesion at screening include tobacco smoking and snuff use, alcohol drinking, lack of fruits/vegetables consumption, and red/processed meat consumption, low spice consumption level, and comorbidities (p-value: <0.001–0.046). The predictive model based on the significant factors has an AUC of 0.74 (0.72 – 0.76) and Youden’s index of 0.27 (0.25-0.29) that is higher than the metrics obtained for the conventional method of risk profiling for oral cancer (Youden’s index: 0.25 (0.23-0.27)).

Conclusions

Risk prediction model has better discrimination and net benefit than the conventional approach for identifying at-risk individuals for oral cancer. This finding supports the potential application of this method for risk stratification during targeted oral cancer screening.