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Record W4406439516 · doi:10.4103/atmr.atmr_176_24

A Systematic Review and Meta-analysis of the Effect of Proton Versus Photon in Prostatic Cancer Patients

2024· review· en· W4406439516 on OpenAlexaboutno aff
Somayah Ali Al-Ghubaishi, Sara Mohammad Altheebi, Zainab Aziz Al-Sahwan, Raghad Althomali, Norah Saeed Kadasah, Yusra Hassan Banoun, Mohammed Ahmed Alsubhi

Bibliographic record

VenueJournal of Advanced Trends in Medical Research · 2024
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisCancerMedicineProstate cancerPhotonOncologyPhysicsInternal medicineOptics

Abstract

fetched live from OpenAlex

Abstract Background: Prostate cancer (PC) is also a common urologic malignancy and an important contributor to cancer deaths amongst males. For PC treatment, radiation therapy (RT) is used frequently with the use of new technologies such as intensity-modulated RT, which helps to deliver radiation concentrated on the tumour avoiding damage of the healthy tissue. Photon therapy can be compared to a modern type of RT known as proton therapy (PT), that can also deliver anticancer radiation, but with less damage to healthy tissues. Nevertheless, the clinical utility of PT in PC remains questionable because the therapy is expensive and there are few comparative trials. The objectives of this systematic review and meta-analysis are to systematically assess the comparative efficacy and toxicity of proton compared with photon therapy in the treatment of localised PC. Methods: Specifically, the methods of these systematic reviews and meta-analyses were identified according to the Cochrane Handbook and the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. After developing the review protocol, it was published on PROSPERO. The trim-and-fill method was then applied to assess if any additional studies needed to be incorporated in an effort to balance potential source of bias that might have pulled the summary odds ratio towards either end of the distribution. These eight sample cohort studies were sourced from the initial PubMed, Web of Sciences as well as Scopus search under the keywords ‘Proton’, ‘Photon’, ‘Prostatic cancer’ and ‘Radiotherapy’. The Newcastle–Ottawa Scale was used to assess the quality of the included studies. Extraction of data was done by four authors, concerning the aspects of study design, patients’ characteristics and treatment results. Sensitivity analyses as well as other statistical analyses were conducted using Review Manager 5.4 and OpenMetaAnalyst software. Results: The meta-analysis consisted of eight researches from different countries including the USA, Austria, Norway and Singapore, which compared proton with photon therapy in patients with PC. Compared with photon therapy, PT decreased radiation of the rectum and bladder by six standardised mean differences on average. The study concluded that proton therapy significantly reduces radiation dose to organs at risk, particularly the rectum and bladder, but no significant differences were observed for intraprostatic lesions or urethra. It was also observed that there were no different levels of tolerance to dose for intraprostatic lesions and the urethra when applying both forms of treatment. Subgroup analyses showed that removing some studies will reduce the heterogeneity and give consistent results. Conclusions: A case of PT seems to have benefits in the reduction of dosage amounts delivered to organs at risk such as the rectum and bladder in the treatment of PC patients. However, no enhancement in managing intraprostatic lesions and the urethra was reported as compared with photon therapy. More comparative studies on bigger patient series and those using a common treatment planning algorithm are still required to confirm our findings and investigate the general applicability of PT in PC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.482
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.540
Teacher spread0.406 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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