Search for authorsSearch for similar articles
0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Longer survival with precision medicine in late-stage cancer patients☆

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          In a per-protocol analysis of molecularly profiled patients with treatment-refractory, end-stage cancer discussed at the National Molecular Tumor Board (NMTB), we aimed to assess the overall survival (OS) outcome of targeted treatment compared with no targeted treatment.

          Materials and methods

          Patients were prospectively included at a single oncological center. Whole exome and RNA sequencing (tumor-normal) were carried out, and cases were presented at the NMTB for discussion of targeted treatment. Treatment was available through a basket trial, by compassionate use or in early clinical trials.

          Results

          One hundred and ninety-six patients were included from 2020 to 2023. In all but three patients a driver variant was disclosed, while 42% had simultaneous affection of more than three oncogenic pathways. In 42% of patients a druggable target was identified but two-thirds did not receive the suggested treatment. The fraction of patients initiating treatment yearly rose from 8% to 22%. For patients treated ( N = 30), the clinical benefit rate was 44% and median time on treatment was 3.5 months. Druggable targets were enriched in lung cancers, while patients receiving or not receiving targeted treatment had similar clinical characteristics. The median OS was longer for patients receiving targeted treatment (15 months), but similar for patients with no druggable target and suggested targeted treatment not initiated (5 and 6 months, respectively) ( P = 0.004). In multivariate analysis, targeted treatment (hazard ratio 0.43, confidence interval 0.25-0.72), few metastatic sites, and adenocarcinoma histology were predictive of improved OS while alterations of the RTK/RAS pathway were prognostically unfavorable.

          Conclusions

          Tissue-agnostic targeted treatment based on molecular tumor profiling is possible in an increasing fraction of end-stage cancer patients. In those who receive targeted treatment, results strongly suggest a significant survival benefit.

          Highlights

          • Impact on patients’ (pts) survival is rarely reported in tissue-agnostic studies of precision medicine.

          • In 196 end-stage cancer pts, we assessed the OS of those treated or not treated with a matched targeted drug.

          • Druggable targets were suggested in 42% but 2/3 were not treated. Median time to treatment failure was 3.5 months.

          • Pts treated with a matched drug survived 2.6× longer. Targeted treatment was the strongest prognostic predictor.

          • The results strongly suggest a survival benefit of precision medicine even in the setting of end-stage cancer.

          Related collections

          Most cited references63

          • Record: found
          • Abstract: found
          • Article: not found

          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

            Assessment of the change in tumour burden is an important feature of the clinical evaluation of cancer therapeutics: both tumour shrinkage (objective response) and disease progression are useful endpoints in clinical trials. Since RECIST was published in 2000, many investigators, cooperative groups, industry and government authorities have adopted these criteria in the assessment of treatment outcomes. However, a number of questions and issues have arisen which have led to the development of a revised RECIST guideline (version 1.1). Evidence for changes, summarised in separate papers in this special issue, has come from assessment of a large data warehouse (>6500 patients), simulation studies and literature reviews. HIGHLIGHTS OF REVISED RECIST 1.1: Major changes include: Number of lesions to be assessed: based on evidence from numerous trial databases merged into a data warehouse for analysis purposes, the number of lesions required to assess tumour burden for response determination has been reduced from a maximum of 10 to a maximum of five total (and from five to two per organ, maximum). Assessment of pathological lymph nodes is now incorporated: nodes with a short axis of 15 mm are considered measurable and assessable as target lesions. The short axis measurement should be included in the sum of lesions in calculation of tumour response. Nodes that shrink to <10mm short axis are considered normal. Confirmation of response is required for trials with response primary endpoint but is no longer required in randomised studies since the control arm serves as appropriate means of interpretation of data. Disease progression is clarified in several aspects: in addition to the previous definition of progression in target disease of 20% increase in sum, a 5mm absolute increase is now required as well to guard against over calling PD when the total sum is very small. Furthermore, there is guidance offered on what constitutes 'unequivocal progression' of non-measurable/non-target disease, a source of confusion in the original RECIST guideline. Finally, a section on detection of new lesions, including the interpretation of FDG-PET scan assessment is included. Imaging guidance: the revised RECIST includes a new imaging appendix with updated recommendations on the optimal anatomical assessment of lesions. A key question considered by the RECIST Working Group in developing RECIST 1.1 was whether it was appropriate to move from anatomic unidimensional assessment of tumour burden to either volumetric anatomical assessment or to functional assessment with PET or MRI. It was concluded that, at present, there is not sufficient standardisation or evidence to abandon anatomical assessment of tumour burden. The only exception to this is in the use of FDG-PET imaging as an adjunct to determination of progression. As is detailed in the final paper in this special issue, the use of these promising newer approaches requires appropriate clinical validation studies.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Maftools: efficient and comprehensive analysis of somatic variants in cancer

              Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.
                Bookmark

                Author and article information

                Contributors
                Journal
                ESMO Open
                ESMO Open
                ESMO Open
                Elsevier
                2059-7029
                03 January 2025
                January 2025
                03 January 2025
                : 10
                : 1
                : 104089
                Affiliations
                [1 ]Department of Oncology and Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark
                [2 ]Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, Aalborg, Denmark
                [3 ]Molecular Diagnostics and Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark
                [4 ]Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
                [5 ]Department of Clinical Genetics and Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark
                [6 ]Department of Pathology, Aalborg University Hospital, Aalborg, Denmark
                Author notes
                [] Correspondence to: Prof. Morten Ladekarl, Department of Oncology, Aalborg University Hospital, Hobrovej 18, 9000 Aalborg, Denmark. Tel: +45-6139-9326 morten.ladekarl@ 123456rn.dk
                [†]

                These authors share first authorship.

                [☆]

                Note: This study was previously presented in part at the ESMO MAP congress 2023. 1

                Article
                S2059-7029(24)01859-3 104089
                10.1016/j.esmoop.2024.104089
                11758131
                39754975
                06569084-e033-4ddb-a3cd-385d91354b67
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Original Article

                precision medicine,prognosis,tissue agnostic,clinical trial,molecular pathway analysis

                Comments

                Comment on this article