Evidence map›Paper›PMID 39611922›Full record

ReviewAsian Pacific journal of cancer prevention : APJCP2024

Scientific Advances in Cancer Detection Using Raman Spectroscopy.

Gourav Kumar Jain, Rajni Verma, Arun Chougule, Bharti Singh

Abstract readReview
In one paragraph

Review in Asian Pacific journal of cancer prevention : APJCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Gourav Kumar JainDepartment of Radiological Physics, SMS Medical College & Hospital, Jaipur-302004, India.
Rajni VermaDepartment of Radiological Physics, SMS Medical College & Hospital, Jaipur-302004, India.
Arun ChouguleSwasthya Kalyan group of Institutions, Jaipur-302022, India.
Bharti SinghDepartment of Chemistry, Indian Institute of Technology Delhi, New Delhi-110016, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThe present study is focused to investigate the role of Raman spectroscopy (RM) for cancer detection.

methodsIn this review, we explored a number of scientific databases including PubMed, Web of Science, Embase and Google Scholar for research studies on Raman spectroscopy for diagnosing cancer. We reported key outcomes of research studies conducted involving Raman spectroscopy for diagnosis of cancer and highlighting the potential of novel Raman spectroscopy for diagnosing cancer in our review.

resultsBased on the available evidence it can be strongly concluded that Raman spectroscopy provide significant information for diagnosing cancer. Numerous comprehensive studies involving living cells in vitro, in-vivo animal models and ex-vivo human tissues pre-clinical Raman experiments are conducted on biological specimens for almost every type of cancer for diagnosing cancer demonstrating the potential for clinical use of Raman spectroscopy. Furthermore, the in-vivo Raman handheld probes are developed and experimentally used for real time detection of human breast and brain tumors with significant sensitivity and specificity. However, it will be important and challenging to explore relevant Raman biomarkers for other types of cancer as well, to distinguish cancer.

conclusionRaman spectroscopy is an effective method and valuable tool in the field of cancer diagnostics. The Raman spectroscopy deserves a place for future in clinics for rapid cancer diagnostics.

Indexed as

NeoplasmsSpectrum Analysis, RamanAnimalsBiomarkers, TumorHumansBiomarkers, TumorcancerDiagnosisRaman Spectroscopyspectrum

Identifiers

PMID39611922
PMCPMC11996111

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Registered trials

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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.