Postapproval trials versus patient registries:comparability of advanced melanoma patients with brain metastases

Postapproval trials and patient registries have their pros and cons in the generation of postapproval data. No direct comparison between clinical outcomes of these data sources currently exists for advanced melanoma patients. We aimed to investigate whether a patient registry can complement or even replace postapproval trials. Postapproval single-arm clinical trial data from the Medicines Evaluation Board and real-world data from the Dutch Melanoma Treatment Registry were used. The study population consisted of advanced melanoma patients with brain metastases treated with targeted therapies (BRAF- or BRAF-MEK inhibitors) in the first line. A Cox hazard regression model and a propensity score matching (PSM) model were used to compare the two patient populations. Compared to patients treated in postapproval trials (n = 467), real-world patients (n = 602) had significantly higher age, higher ECOG performance status, more often ≥3 organ involvement and more symptomatic brain metastases. Lactate dehydrogenase levels were similar between both groups. The unadjusted median overall survival (mOS) in postapproval clinical trial patients was 8.7 (95% CI, 8.1-10.4) months compared to 7.2 (95% CI, 6.5-7.7) months (P < 0.01) in real-world patients. With the Cox hazard regression model, survival was adjusted for prognostic factors, which led to a statistically insignificant difference in mOS for trial and real-world patients of 8.7 (95% CI, 7.9-10.4) months compared to 7.3 (95% CI, 6.3-7.9) months, respectively. The PSM model resulted in 310 matched patients with similar survival (P = 0.9). Clinical outcomes of both data sources were similar. Registries could be a complementary data source to postapproval clinical trials to establish information on clinical outcomes in specific subpopulations

Perceptions of involvement in advance care planning and emotional functioning in patients with advanced cancer

Purpose: Advance Care Planning (ACP) is positively associated with the quality of care, but its impact on emotional functioning is ambiguous. This study investigated the association between perceptions of ACP involvement and emotional functioning in patients with advanced cancer. Methods: This study analyzed baseline data of 1,001 patients of the eQuiPe study, a prospective, longitudinal, multicenter, observational study on quality of care and quality of life in patients with advanced cancer in the Netherlands. Patients with metastatic solid cancer were asked to participate between November 2017 and January 2020. Patients’ perceptions of ACP involvement were measured by three self-administered statements. Emotional functioning was measured by the EORTC-QLQ-C30. A linear multivariable regression analysis was performed while taking gender, age, migrant background, education, marital status, and symptom burden into account. Results: The majority of patients (87%) reported that they were as much involved as they wanted to be in decisions about their future medical treatment and care. Most patients felt that their relatives (81%) and physicians (75%) were familiar with their preferences for future medical treatment and care. A positive association was found between patients’ perceptions of ACP involvement and their emotional functioning (b=0.162, p<0.001, 95%CI[0.095;0.229]) while controlling for relevant confounders. Conclusions: Perceptions of involvement in ACP are positively associated with emotional functioning in patients with advanced cancer. Future studies are needed to further investigate the effect of ACP on emotional functioning. Trial registration number: NTR6584 Date of registration: 30 June 2017 Implications for Cancer Survivors: Patients’ emotional functioning might improve from routine discussions regarding goals of future care. Therefore, integration of ACP into palliative might be promising

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma

Introduction: Predicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumour characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort. Methods: Patients who received first-line anti-PD1±anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT, and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict clinical benefit, defined as stable disease for more than 6 months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-centre-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model. Results: A total of 620 patients were included, of which 59.2% experienced clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95% CI, 0.562–0.652], lower than that of the clinical model (AUROC=0.646 [95% CI, 0.600–0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95% CI, 0.592–0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001). Discussion: The radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma

First-line BRAF/MEK inhibitors versus anti-PD-1 monotherapy in BRAFV600-mutant advanced melanoma patients: a propensity-matched survival analysis

Background: Anti-PD-1 antibodies and BRAF/MEK inhibitors are the two main groups of systemic therapy in the treatment of BRAFV600-mutant advanced melanoma. Until now, data are inconclusive on which therapy to use as first-line treatment. The aim of this study was to use propensity score matching to compare first-line anti-PD-1 monotherapy vs. BRAF/MEK inhibitors in advanced BRAFV600-mutant melanoma patients. Methods: We selected patients diagnosed between 2014 and 2017 with advanced melanoma and a known BRAFV600-mutation treated with first-line BRAF/MEK inhibitors or anti-PD-1 antibodies, registered in the Dutch Melanoma Treatment Registry. Patients were matched based on their propensity scores using the nearest neighbour and the optimal matching method. Results: Between 2014 and 2017, a total of 330 and 254 advanced melanoma patients received BRAF/MEK inhibitors and anti-PD-1 monotherapy as first-line systemic therapy. In the matched cohort, patients receiving anti-PD-1 antibodies as a first-line treatment had a higher median and 2-year overall survival compared to patients treated with first-line BRAF/MEK inhibitors, 42.3 months (95% CI: 37.3-NE) vs. 19.8 months (95% CI: 16.7–24.3) and 85.4% (95% CI: 58.1–73.6) vs. 41.7% (95% CI: 34.2–51.0). Conclusions: Our data suggest that in the matched BRAFV600-mutant advanced melanoma patients, anti-PD-1 monotherapy is the preferred first-line treatment in patients with relatively favourable patient and tumour characteristics

Long-term survival of patients with advanced melanoma treated with BRAF-MEK inhibitors

Recent results of patients with advanced melanoma treated with first-line BRAF-MEK inhibitors in clinical trials showed 5-year survival in one-third of patients with a median overall survival (OS) of more than 2 years. This study aimed to investigate these patients' real-world survival and identify the characteristics of long-term survivors. The study population consisted of patients with advanced cutaneous melanoma with a BRAF-V600 mutated tumor who were treated with first-line BRAF-MEK inhibitors between 2013 and 2017. Long-term survival was defined as a minimum OS of 2 years from start therapy. The median progression-free survival (mPFS) and median OS (mOS) of real-world patients ( n = 435) were respectively 8.0 (95% CI, 6.8-9.4) and 11.7 (95% CI, 10.3-13.5) months. Two-year survival was reached by 28% of the patients, 22% reached 3-year survival and 19% reached 4-year survival. Real-world patients often had brain metastases (41%), stage IV M1c disease (87%), ECOG PS ≥2 (21%), ≥3 organ sites (62%) and elevated LDH of ≥250 U/I (49%). Trial-eligible real-world patients had an mOS of 17.9 months. Patients surviving more than 2 years ( n = 116) more often had an ECOG PS ≤1 (83%), normal LDH (60%), no brain metastases (60%), no liver metastases (63%) and <3 organ sites (60%). Long-term survival of real-world patients treated with first-line BRAF-MEK inhibitors is significantly lower than that of trial patients, which is probably explained by poorer baseline characteristics of patients treated in daily practice. Long-term survivors generally had more favorable characteristics with regard to age, LDH level and metastatic sites, compared to patients not reaching long-term survival

Postapproval trials versus patient registries: comparability of advanced melanoma patients with brain metastases

Postapproval trials and patient registries have their pros and cons in the generation of postapproval data. No direct comparison between clinical outcomes of these data sources currently exists for advanced melanoma patients. We aimed to investigate whether a patient registry can complement or even replace postapproval trials. Postapproval single-arm clinical trial data from the Medicines Evaluation Board and real-world data from the Dutch Melanoma Treatment Registry were used. The study population consisted of advanced melanoma patients with brain metastases treated with targeted therapies (BRAF- or BRAF-MEK inhibitors) in the first line. A Cox hazard regression model and a propensity score matching (PSM) model were used to compare the two patient populations. Compared to patients treated in postapproval trials (n = 467), real-world patients (n = 602) had significantly higher age, higher ECOG performance status, more often ≥3 organ involvement and more symptomatic brain metastases. Lactate dehydrogenase levels were similar between both groups. The unadjusted median overall survival (mOS) in postapproval clinical trial patients was 8.7 (95% CI, 8.1-10.4) months compared to 7.2 (95% CI, 6.5-7.7) months (P < 0.01) in real-world patients. With the Cox hazard regression model, survival was adjusted for prognostic factors, which led to a statistically insignificant difference in mOS for trial and real-world patients of 8.7 (95% CI, 7.9-10.4) months compared to 7.3 (95% CI, 6.3-7.9) months, respectively. The PSM model resulted in 310 matched patients with similar survival (P = 0.9). Clinical outcomes of both data sources were similar. Registries could be a complem

Correction: First-line BRAF/MEK inhibitors versus anti-PD-1 monotherapy in BRAFV600-mutant advanced melanoma patients: a propensity-matched survival analysis (British Journal of Cancer, (2021), 10.1038/s41416-020-01229-1): First-line BRAF/MEK inhibitors versus anti-PD-1 monotherapy in BRAFV600-mutant advanced melanoma patients: a propensity-matched survival analysis (British Journal of Cancer, (2021), 124, 7, (1222-1230), 10.1038/s41416-020-01229-1)

Since the publication of this paper, the authors have noticed an error in the Abstract where the value for the 2-year overall surviva