ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2023
Window therapeutic of extraoral photobiomodulation for prevention of oral mucositis in HSCT patients: additional arm.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Photobiomodulation in the management of oral lesions: a targeted, evidence-based approach.Brazilian oral research · 2026Review
- Preventive versus curative photobiomodulation for oral mucositis in patients with multiple myeloma undergoing hematopoietic stem cell transplantation: which approach is more effective?Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to evaluate the efficacy of 1W extraoral photobiomodulation (EOPBM) and to compare with our previous results of 2W EOPBM and intraoral photobiomodulation (IOPBM) protocols in the management of oral mucositis (OM) related to hematopoietic stem cell transplantation (HSCT).
methodsA total of 30 patients underwent autologous or allogenic HSCT. Experimental protocol of 1W EOPBM was performed daily beginning in the first day of the conditioning regimen until 5 days after transplantation. The application areas included six points on the face and three points on the cervical area. Additional application of IOPBM was performed if patients had ulcered mucositis. Its severity was assessed daily according to WHO (World Health Organization) and NCI (National Cancer Institute) scales. Oral and oropharynx pains were scored daily by visual analogue scale (VAS).
resultsThe 1W EOPBM protocol was well tolerated without any complaints. Of total, 13 patients were male and 17 were female and the mean age was 49.3 years old. Most patients (21 patients - 70%) received autologous HSCT, and 24 patients (80%) underwent myeloablative conditioning (MAC) regime and 6 patients (20%) reduced intensive conditioning regime. Nineteen patients (63.3%) developed OM according to WHO criteria, 3 patients grade I, 10 grade II and 6 grade III. NCI mucositis grades were similar to WHO grades. OM outcomes of 1W EOPBM were similar when compared to our previous groups and no significant differences were observed. No differences were found between pain and the protocols (1W EOPBM, IOPBM and 2W EOPBM).
conclusionThis 1W EOPBM protocol seemed to be as effective as IOPBM and 2W EOPBM in the prevention of OM in HSCT patients. In addition, we might assume that there is a window of application on EOPBM.
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.