ArticleJournal of biophotonics2026
Minimally Invasive Raman Spectroscopy for Detection of Lymph Node Metastasis of Oral Squamous Cell Carcinoma.
Article in Journal of biophotonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lymph node metastasis (LNM) is a critical prognostic factor in oral squamous cell carcinoma (OSCC), yet its preoperative assessment remains challenging. This study evaluated serum and salivary Raman spectroscopy (RS) for LNM detection in OSCC. Serum and saliva samples from 36 OSCC patients [16 node-positive (N+) and 20 node-negative (N0)] and 15 healthy controls were analysed using RS. Classification models were developed using RS data of individual biofluids and with fusion strategies. The serum model identified 87.5% of N+ and 85% of N0 cases, while saliva showed comparable performance for N+ but lower accuracy for N0. Low-level fusion improved N+ classification. Mid-level fusion achieved the best overall performance, correctly identifying 100% of N+ and 85% of N0 cases. Spectral analysis revealed alterations associated with proteins, β-carotenoids, deoxyhaemoglobin and lipids across the study groups. These findings demonstrate the potential of biofluid-based RS for minimally invasive LNM assessment in OSCC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.