Risk prediction by Raman spectroscopy for disease-free survival in oral cancers

In the present study, the potential of Raman spectroscopy (RS) in predicting disease-free survival (DFS) in oral cancer patients has been explored. Raman spectra were obtained from the tumor and contralateral regions of 94 oral squamous cell carcinoma patients. These patients were managed surgically...

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Bibliographic Details
Published in:Lasers in medical science 2021-10, Vol.36 (8), p.1691-1700
Main Authors: Bhattacharjee, Atanu, Hole, Arti, Malik, Akshat, Sahu, Aditi, Singh, S. P., Deshmukh, Atul, Nair, Sudhir, Chaturvedi, Pankaj, Murali Krishna, C.
Format: Article
Language:English
Subjects:
Cancer
Confidence intervals
Dentistry
Lasers
Medicine
Medicine & Public Health
Optical Devices
Optics
Oral cancer
Oral carcinoma
Oral squamous cell carcinoma
Original Article
Performance prediction
Photonics
Prediction models
Quantum Optics
Raman spectra
Raman spectroscopy
Spectroscopy
Spectrum analysis
Survival
Survival analysis
Tumors
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Summary:In the present study, the potential of Raman spectroscopy (RS) in predicting disease-free survival (DFS) in oral cancer patients has been explored. Raman spectra were obtained from the tumor and contralateral regions of 94 oral squamous cell carcinoma patients. These patients were managed surgically and recommended for adjuvant therapy. The Cox proportional survival analysis was carried out to identify the spectral regions that can be correlated to DFS. The survival analysis was performed with 95% confidence intervals, hazard ratio, and p -values in the 1200-1800 cm −1 spectral region. Out of a total of 182 spectral points, 76 were found to be correlating with DFS, suggesting their utility to predict the patient outcome. The cut-off points of each correlating RS-point values were defined and tested towards predicting the DFS. The performance of predicting the power of spectral points was validated through Brier value, and it was found to be closer to the actual progression. The 76 spectral points identified from the tumors have the potential to accurately predict DFS in oral squamous cell carcinoma through a relatively simplistic prediction model in the absence of confounding factors.
ISSN:0268-8921
1435-604X
DOI:10.1007/s10103-021-03276-3