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- Holmberg, Carl Jacob, et al.
(författare)
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The efficacy of immune checkpoint blockade for melanoma in-transit with or without nodal metastases - A multicenter cohort study
- 2022
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Ingår i: EUROPEAN JOURNAL OF CANCER. - : Elsevier BV. - 0959-8049 .- 1879-0852. ; 40:16
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Guidelines addressing melanoma in-transit metastasis (ITM) recommend immune checkpoint inhibitors (ICI) as a first-line treatment option, despite the fact that there are no efficacy data available from prospective trials for exclusively ITM disease. The study aims to analyze the outcome of patients with ITM treated with ICI based on data from a large cohort of patients treated at international referral clinics. Methods: A multicenter retrospective cohort study of patients treated between January 2015 and December 2020 from Australia, Europe, and the USA, evaluating treatment with ICI for ITM with or without nodal involvement (AJCC8 N1c, N2c, and N3c) and without distant disease (M0). Treatment was with PD-1 inhibitor (nivolumab or pembrolizumab) and/or CTLA-4 inhibitor (ipilimumab). The response was evaluated according to the RECIST criteria modified for cutaneous lesions. Results: A total of 287 patients from 21 institutions in eight countries were included. Immunotherapy was first-line treatment in 64 (22%) patients. PD-1 or CTLA-4 inhibitor monotherapy was given in 233 (81%) and 23 (8%) patients, respectively, while 31 (11%) received both in combination. The overall response rate was 56%, complete response (CR) rate was 36%, and progressive disease (PD) rate was 32%. Median PFS was ten months (95% CI 7.4-12.6 months) with a one-, two-, and five-year PFS rate of 48%, 33%, and 18%, respectively. Median MSS was not reached, and the one-, two-, and five-year MSS rates were 95%, 83%, and 71%, respectively. Conclusion: Systemic immunotherapy is an effective treatment for melanoma ITM. Future studies should evaluate the role of systemic immunotherapy in the context of multimodality therapy, including locoregional treatments such as surgery, intralesional therapy, and regional therapies.
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- Gerdtsson, Axel, et al.
(författare)
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Validation of a prediction model for post-chemotherapy fibrosis in nonseminoma patients
- 2023
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Ingår i: Bju International. - 1464-4096 .- 1464-410X. ; 132:3, s. 329-336
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Tidskriftsartikel (refereegranskat)abstract
- Objective To validate Vergouwe's prediction model using the Swedish and Norwegian Testicular Cancer Group (SWENOTECA) RETROP database and to define its clinical utility. Materials and methods Vergouwe's prediction model for benign histopathology in post-chemotherapy retroperitoneal lymph node dissection (PCRPLND) uses the following variables: presence of teratoma in orchiectomy specimen; pre-chemotherapy level of alphafetoprotein; b-Human chorionic gonadotropin and lactate dehydrogenase; and lymph node size pre- and postchemotherapy. Our validation cohort consisted of patients included in RETROP, a prospective population-based database of patients in Sweden and Norway with metastatic nonseminoma, who underwent PC-RPLND in the period 2007-2014. Discrimination and calibration analyses were used to validate Vergouwe's prediction model results. Calibration plots were created and a Hosmer-Lemeshow test was calculated. Clinical utility, expressed as opt-out net benefit (NBopt-out), was analysed using decision curve analysis. Results Overall, 284 patients were included in the analysis, of whom 130 (46%) had benign histology after PC-RPLND. Discrimination analysis showed good reproducibility, with an area under the receiver-operating characteristic curve (AUC) of 0.82 (95% confidence interval 0.77-0.87) compared to Vergouwe's prediction model (AUC between 0.77 and 0.84). Calibration was acceptable with no recalibration. Using a prediction threshold of 70% for benign histopathology, NBopt-out was 0.098. Using the model and this threshold, 61 patients would have been spared surgery. However, only 51 of 61 were correctly classified as benign. Conclusions The model was externally validated with good reproducibility. In a clinical setting, the model may identify patients with a high chance of benign histopathology, thereby sparing patients of surgery. However, meticulous follow-up is required.
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