Efficacy of Photodynamic Therapy with Chlorine-Based Photosensitizer in the Treatment of Basal Cell Carcinomas
Bibliographic record
Abstract
The aim of this study is to evaluate a safety and antitumor efficacy of photodynamic therapy (PDT) with chlorine-based photosensitizer (PS) for treatment patients with basal cell skin carcinomas (BCC). Material and Methods: The work was performed on the basis of the Department of hyperthermia and photodynamic therapy. The object of the study were 172 patients with a verified diagnosis of BCC (T1N0M0, I stage), who received treatment from 2007 to 2022. PS «Photolon» (RUE «Belmedpreparaty», Republic of Belarus) was administrated intravenously at a dose of 2.0-2.5 mg/kg. The session of PDT was performed 2.5-3 h after intravenous injection of PS using semiconductor lasers (λ=660±5 nm) with exposure doses 50-250 J/cm² and power density – 0.15-0.5 W/cm². Frequency and severity of side effects after treatment session was assessed based on the criteria CTCAE (Version 4.03; 2010). The antitumor efficacy was evaluated 3 months after treatment. Clinical outcome was evaluated visually and morphologically by cytological or histopathological examination. Performance criteria were as follows (according to WHO, 1979). Results: The phenomenon of skin phototoxicity due to violation of the light regime (hyperemia, burning, slight swelling of the soft tissues of the face; CTCAE, I-II grades) was registered in 5.8% of cases (n=10). Serious adverse reactions (anaphylactic shock, Quincke's edema, severe pain syndrome) after the administration of PS and photoirradiation were not identified. Complete and partial regressions of tumors was observed in 93.0% and 4.7% of patients, respectively. The objective answer was 97.7%. The frequency of local relapses of the disease 1, 2, 3, 4 and 5 years after PDT was 3.1%, 3.1%, 4.6%, 4.6% and 6.9%, respectively. Сonclusion: PDT is a well-tolerated and highly effective therapeutic option in patients with BCC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".