A phase 2 trial combining afatinib with cetuximab in patients with EGFR exon 20 insertion-positive non-small cell lung cancer.

BACKGROUND: Epidermal growth factor receptor (EGFR) exon 20 insertion (ex20ins) mutations are the third most common EGFR mutations in patients with non-small cell lung cancer (NSCLC) and are associated with primary resistance to EGFR tyrosine kinase inhibitors (TKIs). There is evidence of activity of combining EGFR TKIs with monoclonal antibodies. This study reports on the efficacy and safety of afatinib in combination with cetuximab. METHODS: In this single-arm phase 2 trial, patients with advanced NSCLC harboring an EGFR ex20ins mutation were treated with afatinib 40 mg once daily in combination with cetuximab 500 mg/m2 every 2 weeks. The primary end point was disease control rate (DCR) at 18 weeks of treatment. RESULTS: Thirty-seven patients started treatment, with a median age of 65 years (range, 40-80 years), 78% female, and 95% White. The study achieved its primary end point with a DCR of 54% at 18 weeks, an overall response rate (ORR) of 43%, and a 32% confirmed ORR. Best responses were partial (n = 16), stable (n = 16), progressive disease (n = 2), or not evaluable (n = 3). Median progression-free survival was 5.5 months (95% CI, 3.7-8.3 months) and median overall survival was 16.8 months (95% CI, 10.7-25.8 months). The most common treatment-related adverse events (TRAEs) were diarrhea (70%), rash (65%), dry skin (59%), paronychia (54%), and erythema (43%). Grade 3 TRAEs were reported in 54% of all patients. CONCLUSIONS: Combination treatment with afatinib and cetuximab demonstrated antitumor activity with a DCR of 54% at 18 weeks and a 32% confirmed ORR. Toxicity was significant, although manageable, after dose reduction.

External Quality Assessment on Molecular Tumor Profiling with Circulating Tumor DNA-Based Methodologies Routinely Used in Clinical Pathology within the COIN Consortium.

BACKGROUND: Identification of tumor-derived variants in circulating tumor DNA (ctDNA) has potential as a sensitive and reliable surrogate for tumor tissue-based routine diagnostic testing. However, variations in pre(analytical) procedures affect the efficiency of ctDNA recovery. Here, an external quality assessment (EQA) was performed to determine the performance of ctDNA mutation detection work flows that are used in current diagnostic settings across laboratories within the Dutch COIN consortium (ctDNA on the road to implementation in The Netherlands). METHODS: Aliquots of 3 high-volume diagnostic leukapheresis (DLA) plasma samples and 3 artificial reference plasma samples with predetermined mutations were distributed among 16 Dutch laboratories. Participating laboratories were requested to perform ctDNA analysis for BRAF exon 15, EGFR exon 18-21, and KRAS exon 2-3 using their regular circulating cell-free DNA (ccfDNA) analysis work flow. Laboratories were assessed based on adherence to the study protocol, overall detection rate, and overall genotyping performance. RESULTS: A broad range of preanalytical conditions (e.g., plasma volume, elution volume, and extraction methods) and analytical methodologies (e.g., droplet digital PCR [ddPCR], small-panel PCR assays, and next-generation sequencing [NGS]) were used. Six laboratories (38%) had a performance score of >0.90; all other laboratories scored between 0.26 and 0.80. Although 13 laboratories (81%) reached a 100% overall detection rate, the therapeutically relevant EGFR p.(S752_I759del) (69%), EGFR p.(N771_H773dup) (50%), and KRAS p.(G12C) (48%) mutations were frequently not genotyped accurately. CONCLUSIONS: Divergent (pre)analytical protocols could lead to discrepant clinical outcomes when using the same plasma samples. Standardization of (pre)analytical work flows can facilitate the implementation of reproducible liquid biopsy testing in the clinical routine.

Blood platelet RNA profiles do not enable for nivolumab response prediction at baseline in patients with non-small cell lung cancer.

BACKGROUND: Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content. OBJECTIVE: We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses. METHODS: We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm. RESULTS: We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63-0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51-0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45-0.70, n = 107 samples)), employing a five-RNAs biomarker panel. CONCLUSIONS: We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass.

OBJECTIVE: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). METHODS: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. RESULTS: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. CONCLUSION: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

Tumour-educated platelets for breast cancer detection: biological and technical insights.

BACKGROUND: Studies have shown that blood platelets contain tumour-specific mRNA profiles tumour-educated platelets (TEPs). Here, we aim to train a TEP-based breast cancer detection classifier. METHODS: Platelet mRNA was sequenced from 266 women with stage I-IV breast cancer and 212 female controls from 6 hospitals. A particle swarm optimised support vector machine (PSO-SVM) and an elastic net-based classifier (EN) were trained on 71% of the study population. Classifier performance was evaluated in the remainder (29%) of the population, followed by validation in an independent set (37 cases and 36 controls). Potential confounding was assessed in post hoc analyses. RESULTS: Both classifiers reached an area under the curve (AUC) of 0.85 upon internal validation. Reproducibility in the independent validation set was poor with an AUC of 0.55 and 0.54 for the PSO-SVM and EN classifier, respectively. Post hoc analyses indicated that 19% of the variance in gene expression was associated with hospital. Genes related to platelet activity were differentially expressed between hospitals. CONCLUSIONS: We could not validate two TEP-based breast cancer classifiers in an independent validation cohort. The TEP protocol is sensitive to within-protocol variation and revision might be necessary before TEPs can be reconsidered for breast cancer detection.

A review on genetic alterations in CNS metastases related to breast cancer treatment. Is there a role for liquid biopsies in CSF?

Acquired mutations or altered gene expression patterns in brain metastases (BM) and/or leptomeningeal metastases (LM) of breast cancer may play a role in therapy-resistance and offer new molecular targets and treatment options. Despite expanding knowledge of genetic alterations in breast cancer and their metastases, clinical applications for patients with central nervous system (CNS) metastases are currently limited. An emerging tool are DNA-techniques that may detect genetic alterations of the CNS metastases in the cerebrospinal fluid (CSF). In this review we discuss genetic studies in breast cancer and CNS metastases and the role of liquid biopsies in CSF.

Dutch National Round Robin Trial on Plasma-Derived Circulating Cell-Free DNA Extraction Methods Routinely Used in Clinical Pathology for Molecular Tumor Profiling.

BACKGROUND: Efficient recovery of circulating tumor DNA (ctDNA) depends on the quantity and quality of circulating cell-free DNA (ccfDNA). Here, we evaluated whether various ccfDNA extraction methods routinely applied in Dutch laboratories affect ccfDNA yield, ccfDNA integrity, and mutant ctDNA detection, using identical lung cancer patient-derived plasma samples. METHODS: Aliquots of 4 high-volume diagnostic leukapheresis plasma samples and one artificial reference plasma sample with predetermined tumor-derived mutations were distributed among 14 Dutch laboratories. Extractions of ccfDNA were performed according to local routine standard operating procedures and were analyzed at a central reference laboratory for mutant detection and assessment of ccfDNA quantity and integrity. RESULTS: Mutant molecule levels in extracted ccfDNA samples varied considerably between laboratories, but there was no indication of consistent above or below average performance. Compared to silica membrane-based methods, samples extracted with magnetic beads-based kits revealed an overall lower total ccfDNA yield (-29%; P < 0.0001) and recovered fewer mutant molecules (-41%; P < 0.01). The variant allelic frequency and sample integrity were similar. In samples with a higher-than-average total ccfDNA yield, an augmented recovery of mutant molecules was observed. CONCLUSIONS: In the Netherlands, we encountered diversity in preanalytical workflows with potential consequences on mutant ctDNA detection in clinical practice. Silica membrane-based methodologies resulted in the highest total ccfDNA yield and are therefore preferred to detect low copy numbers of relevant mutations. Harmonization of the extraction workflow for accurate quantification and sensitive detection is required to prevent introduction of technical divergence in the preanalytical phase and reduce interlaboratory discrepancies.

An Automated Correction Algorithm (ALPACA) for ddPCR Data Using Adaptive Limit of Blank and Correction of False Positive Events Improves Specificity of Mutation Detection.

BACKGROUND: Bio-Rad droplet-digital PCR is a highly sensitive method that can be used to detect tumor mutations in circulating cell-free DNA (cfDNA) of patients with cancer. Correct interpretation of ddPCR results is important for optimal sensitivity and specificity. Despite its widespread use, no standardized method to interpret ddPCR data is available, nor have technical artifacts affecting ddPCR results been widely studied. METHODS: False positive rates were determined for 6 ddPCR assays at variable amounts of input DNA, revealing polymerase induced false positive events (PIFs) and other false positives. An in silico correction algorithm, known as the adaptive LoB and PIFs: an automated correction algorithm (ALPACA), was developed to remove PIFs and apply an adaptive limit of blank (LoB) to individual samples. Performance of ALPACA was compared to a standard strategy (no PIF correction and static LoB = 3) using data from commercial reference DNA, healthy volunteer cfDNA, and cfDNA from a real-life cohort of 209 patients with stage IV nonsmall cell lung cancer (NSCLC) whose tumor and cfDNA had been molecularly profiled. RESULTS: Applying ALPACA reduced false positive results in healthy cfDNA compared to the standard strategy (specificity 98 vs 88%, P = 10-5) and stage IV NSCLC patient cfDNA (99 vs 93%, P = 10-11), while not affecting sensitivity in commercial reference DNA (70 vs 68% P = 0.77) or patient cfDNA (82 vs 88%, P = 0.13). Overall accuracy in patient samples was improved (98 vs 92%, P = 10-7). CONCLUSIONS: Correction of PIFs and application of an adaptive LoB increases specificity without a loss of sensitivity in ddPCR, leading to a higher accuracy in a real-life cohort of patients with stage IV NSCLC.

Validation of a clinical blood-based decision aid to guide immunotherapy treatment in patients with non-small cell lung cancer.

BACKGROUND: The widespread introduction of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has led to durable responses but still many patients fail and are treated beyond progression. OBJECTIVE: This study investigated whether readily available blood-based tumor biomarkers allow accurate detection of early non-responsiveness, allowing a timely switch of therapy and cost reduction. METHODS: In a prospective, observational study in patients with NSCLC treated with nivolumab or pembrolizumab, five serum tumor markers were measured at baseline and every other week. Six months disease control as determined by RECIST was used as a measure of clinical response. Patients with a disease control <  6 months were deemed non-responsive. For every separate tumor marker a criterion for predicting of non-response was developed. Each marker test was defined as positive (predictive of non-response) if the value of that tumor marker increased at least 50% from the value at baseline and above a marker dependent minimum value to be determined. Also, tests based on combination of multiple markers were designed. Specificity and sensitivity for predicting non-response was calculated and results were validated in an independent cohort. The target specificity of the test for detecting non-response was set at >  95%, in order to allow its safe use for treatment decisions. RESULTS: A total of 376 patients (training cohort: 180, validation cohort: 196) were included in our analysis. Results for the specificity of the single marker tests in the validation set were CEA: 98·3% (95% CI: 90·9-100%), NSE: 96·5% (95% CI: 87·9-99·6%), SCC: 96·5% (95% CI: 88·1-99·6%), Cyfra21·1 : 91.8% (95% CI: 81·9-97·3%), and CA125 : 86·0% (95% CI: 74·2-93·7%). A test based on the combination of Cyfra21.1, CEA and NSE accurately predicted non-response in 32.3% (95% CI 22.6-43.1%) of patients 6 weeks after start of immunotherapy. Survival analysis showed a significant difference between predicted responders (Median PFS: 237 days (95% CI 184-289 days)) and non-responders (Median PFS: 58 days (95% CI 46-70 days)) (p <  0.001). CONCLUSIONS: Serum tumor marker based tests can be used for accurate detection of non-response in NSCLC, thereby allowing early and safe discontinuation of immunotherapy in a significant subset of patients.

The diagnostic accuracy of human epididymis protein 4 (HE4) for discriminating between benign and malignant pelvic masses: a systematic review and meta-analysis.

INTRODUCTION: Many women with benign pelvic masses, suspected of ovarian cancer, are unnecessarily referred for treatment at specialized centers. There is an unmet clinical need to improve diagnostic assessment in these patients. Our objective was to obtain summary estimates of the accuracy of human epididymis protein (HE4) for diagnosing ovarian cancer and to compare the performance of HE4 with that of cancer antigen 125 (CA125). MATERIAL AND METHODS: We searched PubMed, Ovid and Scopus using search terms for "pelvic masses" and "HE4", to identify studies that evaluated HE4 for diagnosing malignant ovarian masses, in adult women presenting with a pelvic mass, suspected of ovarian cancer, and with diagnosis confirmed by histopathology. Screening, data extraction and Risk of Bias assessment with the QUADAS-2 tool were done independently by two authors. We performed a meta-analysis of the accuracy of HE4 and CA125 using a random-effects bivariate logit-normal model. A study protocol was registered at PROSPERO (CRD42020158073). RESULTS: In the 17 eligible studies, which included 3404 patients, ovarian cancer prevalence ranged from 15% to 71%. Overall, the studies were heterogeneous. All studies seemed to have recruited patients in specialized settings. A meta-analysis of seven HE4 studies resulted in a mean sensitivity of 79.4% (95% confidence interval [CI] 74.1%-83.8%) and a mean specificity of 84.1% (95% CI 79.6%-87.8%), for cut-off values of 67-72 pmol/L. Based on eight studies, the mean sensitivity of CA125 was 81.4% (95% CI 74.6%-86.2%) and the mean specificity was 56.8% (95% CI 47.9%-65.4%), at a cut-off of 35 U/ml. Given a 40% ovarian cancer prevalence, the positive predictive value (PPV) for HE4 would be 76.9% (71.9%-81.2%) vs 55.6% (50.2%-60.9%) for CA125. The negative predictive value (NPV) would be 85.9 (82.8%-88.6%) and 81.9% (76.2%-86.4%), respectively. At a 15% prevalence, the NPV would be 95.8% (95% CI 94.4%-96.7%) for HE4 and 94.4% (95% CI 92.3%-96.0%) for CA125. The PPV would be 46.9% (40.4%-53.4%) and 24.9% (21.1%-29.2%), respectively. CONCLUSIONS: HE4 had higher specificity and similar sensitivity compared with CA125. At high prevalence, PPV was also higher for HE4, but at low prevalence, it had a similar NPV to CA125. The field would benefit from studies conducted in general settings.

Design and implementation of quality control plans that integrate moving average and internal quality control: incorporating the best of both worlds.

Background New moving average quality control (MA QC) optimization methods have been developed and are available for laboratories. Having these methods will require a strategy to integrate MA QC and routine internal QC. Methods MA QC was considered only when the performance of the internal QC was limited. A flowchart was applied to determine, per test, whether MA QC should be considered. Next, MA QC was examined using the MA Generator (www.huvaros.com), and optimized MA QC procedures and corresponding MA validation charts were obtained. When a relevant systematic error was detectable within an average daily run, the MA QC was added to the QC plan. For further implementation of MA QC for continuous QC, MA QC management software was configured based on earlier proposed requirements. Also, protocols for the MA QC alarm work-up were designed to allow the detection of temporary assay failure based on previously described experiences. Results Based on the flowchart, 10 chemistry, two immunochemistry and six hematological tests were considered for MA QC. After obtaining optimal MA QC settings and the corresponding MA validation charts, the MA QC of albumin, bicarbonate, calcium, chloride, creatinine, glucose, magnesium, potassium, sodium, total protein, hematocrit, hemoglobin, MCH, MCHC, MCV and platelets were added to the QC plans. Conclusions The presented method allows the design and implementation of QC plans integrating MA QC for continuous QC when internal QC has limited performance.

Food-effect study on uracil and dihydrouracil plasma levels as marker for dihydropyrimidine dehydrogenase activity in human volunteers.

AIMS: This study aimed to determine the effect of food intake on uracil and dihydrouracil plasma levels. These levels are a promising marker for dihydropyrimidine dehydrogenase activity and for individualizing fluoropyrimidine anticancer therapy. METHODS: A randomized, cross-over study in 16 healthy volunteers was performed, in which subjects were examined in fasted and fed state on two separate days. In fed condition, a high-fat, high-caloric breakfast was consumed between 8:00 h and 8:30 h. Whole blood for determination of uracil, dihydrouracil and uridine plasma levels was drawn on both test days at predefined time points between 8:00 h and 13:00 h. RESULTS: Uracil levels were statistically significantly different between fasting and fed state. At 13:00 h, the mean uracil level in fasting state was 12.6 ± 3.7 ng ml-1 and after a test meal 9.4 ± 2.6 ng ml-1 (P < 0.001). Dihydrouracil levels were influenced by food intake as well (mean dihydrouracil level at 13:00 h in fasting state 147.0 ± 36.4 ng ml-1 and in fed state 85.7 ± 22.1 ng ml-1 , P < 0.001). Uridine plasma levels showed curves with similar patterns as for uracil. CONCLUSIONS: It was shown that both uracil and dihydrouracil levels were higher in fasting state than in fed state. This is hypothesized to be an direct effect of uridine plasma levels, which were previously shown to be elevated in fasting state and reduced after intake of food. These findings show that, when assessing plasma uracil and dihydrouracil levels for adaptive fluoropyrimidine dosing in clinical practice, sampling should be done between 8:00 h and 9:00 h after overnight fasting to avoid bias caused by circadian rhythm and food effects.

A proteomics-based approach identifies secreted protein acidic and rich in cysteine as a prognostic biomarker in malignant pleural mesothelioma.

BACKGROUND: We aimed to identify prognostic blood biomarkers using proteomics-based approaches in malignant pleural mesothelioma (MPM). METHODS: Plasma samples from 12 MPM patients were used for exploratory mass spectrometry and ELISA analyses. The significance of secreted protein acidic and rich in cysteine (SPARC) was examined in sera from a Dutch series (n=97). To determine the source of the circulating SPARC, we investigated SPARC expression in MPM tumours and healthy controls, as well as the expression and secretion from cell lines and xenografts. RESULTS: Secreted protein acidic and rich in cysteine was identified as a putative prognostic marker in plasma. Validation in the Dutch series showed that the median survival was higher in patients with low SPARC compared with those with high SPARC (19.0 vs 8.8 months; P=0.01). In multivariate analyses, serum SPARC remained as an independent predictor (HR 1.55; P=0.05). In MPM tumour samples, SPARC was present in the tumour cells and stromal fibroblasts. Cellular SPARC expression was higher in 5 out of 7 cell lines compared with two immortalized mesothelial lines. Neither cell lines nor xenograft tumours secreted detectable SPARC. CONCLUSIONS: Low circulating SPARC was associated with favourable prognosis. Secreted protein acidic and rich in cysteine was present in both tumour cells and stromal fibroblasts; and our in vitro and in vivo experiments suggest that stromal fibroblasts are a potential source of circulating SPARC.

Case Report of a Fatal Serious Adverse Event Upon Administration of T Cells Transduced With a MART-1-specific T-cell Receptor.

Here, we describe a fatal serious adverse event observed in a patient infused with autologous T-cell receptor (TCR) transduced T cells. This TCR, originally obtained from a melanoma patient, recognizes the well-described HLA-A*0201 restricted 26-35 epitope of MART-1, and was not affinity enhanced. Patient 1 with metastatic melanoma experienced a cerebral hemorrhage, epileptic seizures, and a witnessed cardiac arrest 6 days after cell infusion. Three days later, the patient died from multiple organ failure and irreversible neurologic damage. After T-cell infusion, levels of IL-6, IFN-γ, C-reactive protein (CRP), and procalcitonin increased to extreme levels, indicative of a cytokine release syndrome or T-cell-mediated inflammatory response. Infused T cells could be recovered from blood, broncho-alveolar lavage, ascites, and after autopsy from tumor sites and heart tissue. High levels of NT-proBNP indicate semi-acute heart failure. No cross reactivity of the modified T cells toward a beating cardiomyocyte culture was observed. Together, these observations suggest that high levels of inflammatory cytokines alone or in combination with semi-acute heart failure and epileptic seizure may have contributed substantially to the occurrence of the acute and lethal event. Protocol modifications to limit the risk of T-cell activation-induced toxicity are discussed.

Squamous Cell Carcinoma Antigen in the Follow-up of Patients With Head and Neck Cancer.

OBJECTIVE: to determine if the tumor marker squamous cell carcinoma antigen (SCC-Ag) observed over time may contribute to the early detection of recurrence, metastasis, and second primary tumors in the follow-up of patients with head and neck squamous cell carcinoma (HNSCC). STUDY DESIGN: A retrospective analysis of patients with HNSCC and at least one SCC-Ag measurement was conducted. Hazard ratios (HRs) were used to determine the correlation between SCC-Ag and an event. SETTING: patients with HNSCC, treated in the Antoni van Leeuwenhoek Hospital in The Netherlands between 2010 and 2020 were used for the analysis. METHODS: Data from 789 patients were used on event-free survival (EFS) with time-dependent Cox models. In addition to current (most recent) SCC-Ag (also dichotomized into high and low as done for clinical practice), average SCC-Ag and change between SCC-Ag measurements (delta SCC-Ag) were considered, using restricted cubic splines to explore nonlinear relationships. RESULTS: Dichotomized SCC-Ag values (HR = 3.01, 95% confidence interval [CI]: 2.17-4.18) and the delta SCC-Ag (HR = 1.15, 95% CI: 1.07-1.22) predicted EFS better than models using the cumulative average or current value of SCC-Ag, also after adjusting for tumor site, stage, age, and gender. A strong association was observed when using delta SCC-Ag as a linear predictor in the subgroup of oropharynx patients (HR = 4.88, 95% CI: 2.71-8.79). CONCLUSION: Dichotomized and delta SCC-Ag values can be important markers for EFS, during the follow-up of patients treated for HNSCC. These results were more evident in patients with oropharyngeal cancer.

Can blood-based markers predict RECIST progression in non-small cell lung cancer treated with immunotherapy?

PURPOSE: In this study, we aimed to evaluate the potential of routine blood markers, serum tumour markers and their combination in predicting RECIST-defined progression in patients with stage IV non-small cell lung cancer (NSCLC) undergoing treatment with immune checkpoint inhibitors. METHODS: We employed time-varying statistical models and machine learning classifiers in a Monte Carlo cross-validation approach to investigate the association between RECIST-defined progression and blood markers, serum tumour markers and their combination, in a retrospective cohort of 164 patients with NSCLC. RESULTS: The performance of the routine blood markers in the prediction of progression free survival was moderate. Serum tumour markers and their combination with routine blood markers generally improved performance compared to routine blood markers alone. Elevated levels of C-reactive protein (CRP) and alkaline phosphatase (ALP) ranked as the top predictive routine blood markers, and CYFRA 21.1 was consistently among the most predictive serum tumour markers. Using these classifiers to predict overall survival yielded moderate to high performance, even when cases of death-defined progression were excluded. Performance varied across the treatment journey. CONCLUSION: Routine blood tests, especially when combined with serum tumour markers, show moderate predictive value  of RECIST-defined progression in NSCLC patients receiving immune checkpoint inhibitors. The relationship between overall survival and RECIST-defined progression may be influenced by confounding factors.

A scenario-drafting study to explore potential future implementation pathways of circulating tumor DNA testing in oncology.

Circulating tumor DNA (ctDNA) detection has multiple promising applications in oncology, but the road toward implementation in clinical practice is unclear. We aimed to support the implementation process by exploring potential future pathways of ctDNA testing. To do so, we studied four ctDNA-testing applications in two cancer types and elicited opinions from 30 ctDNA experts in the Netherlands. Our results showed that the current available evidence differed per application and cancer type. Tumor profiling and monitoring treatment response were found most likely to be implemented in non-small cell lung cancer (NSCLC) within 5 years. For colorectal cancer, applications of ctDNA testing were found to be at an early stage in the implementation process. Demonstrating clinical utility was found a key aspect for successful implementation, but there was no consensus regarding the evidence requirements. The next step toward implementation is to define how clinical utility of biomarkers should be evaluated. Finally, these data indicate that specific challenges for each clinical application and tumor type should be appropriately addressed in a deliberative process involving all stakeholders to ensure implementation of ctDNA testing and timely access for patients.

A Micro-Costing Framework for Circulating Tumor DNA Testing in Dutch Clinical Practice.

Circulating tumor DNA (ctDNA) is a promising new biomarker with multiple potential applications in cancer care. Estimating total cost of ctDNA testing is necessary for reimbursement and implementation, but challenging because of variations in workflow. We aimed to develop a micro-costing framework for consistent cost calculation of ctDNA testing. First, the foundation of the framework was built, based on the complete step-wise diagnostic workflow of ctDNA testing. Second, the costing method was set up, including costs for personnel, materials, equipment, overhead, and failures. Third, the framework was evaluated by experts and applied to six case studies, including PCR-, mass spectrometry-, and next-generation sequencing-based platforms, from three Dutch hospitals. The developed ctDNA micro-costing framework includes the diagnostic workflow from blood sample collection to diagnostic test result. The framework was developed from a Dutch perspective and takes testing volume into account. An open access tool is provided to allow for laboratory-specific calculations to explore the total costs of ctDNA testing specific workflow parameters matching the setting of interest. It also allows to straightforwardly assess the impact of alternative prices or assumptions on the cost per sample by simply varying the input parameters. The case studies showed a wide range of costs, from €168 to €7638 ($199 to $9124) per sample, and generated information. These costs are sensitive to the (coverage of) platform, setting, and testing volume.