ArticleInternational journal of nanomedicine2022
Surface-Enhanced Raman Spectroscopy of Pretreated Plasma Samples Predicts Disease Recurrence in Muscle-Invasive Bladder Cancer Patients Undergoing Neoadjuvant Chemotherapy and Radical Cystectomy.
Article in International journal of nanomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 5 citations in OpenAlex.
- Advancements and prospects of Raman spectroscopy in urological tumors: a bibliometric analysis.Lasers in medical science · 2023Review
- Prediction of the postoperative prognosis in patients with non-muscle-invasive bladder cancer based on preoperative serum surface-enhanced Raman spectroscopy.Biomedical optics express · 2022Article
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11 authors at 1 institution in 1 country.
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Abstract
Objective: To explore the value of surface-enhanced Raman spectroscopy analysis of pretreated plasma samples in prediction of bladder cancer (BCa) recurrence after neoadjuvant chemotherapy (NAC) and radical cystectomy (RC). Patients and Methods: SERS was used to analyze plasma samples collected before biopsy and treatment in BCa patients undergoing NAC and RC. The value of clinicopathological parameters and distinctive SERS peaks in the prediction of disease recurrence were analyzed in Cox regression proportional hazard analysis and Log rank test. Principal component analysis and linear discriminant analysis (PCA-LDA) were employed to process spectral data and construct diagnostic algorithms. Results: A total of 88 patients with 440 plasma SERS spectra were collected. The SRES spectra from recurrent patients were compared with patients who remained recurrence free. The SERS demonstrated higher levels of circulating free nucleic acid components in recurrent population, which is represented by significantly higher intensities at SERS peaks of 725 cm Conclusion: We show that SERS analysis of plasma before NAC treatment can accurately classify patients with different risks of disease recurrence after surgery and improve the power of clinicopathological predictive models, thus refining clinical decision-making.
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