1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Competing Risk Analysis of Outcomes of Unresectable Pancreatic Cancer Patients Undergoing Definitive Radiotherapy

      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

          Purpose

          We investigated potential factors, including clinicopathological features, treatment modalities, neutrophil-to-lymphocyte ratio (NLR), carbohydrate antigen (CA) 19-9 level, tumor responses correlating with overall survival (OS), local progression (LP), and distant metastases (DMs), in patients with locally advanced pancreatic cancer (LAPC) who received definitive radiotherapy (RT).

          Methods

          We retrospectively analyzed demographic characteristics; biologically effective doses (BED 10, calculated with an α/β of 10) of RT; and clinical outcomes of 57 unresectable LAPC (all pancreatic adenocarcinoma) patients receiving definitive RT using modern techniques with and without systemic therapy between January 2009 and March 2019 at our institution. We used Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 to evaluate the radiographic tumor response after RT. The association between prognostic factors and OS was assessed using the Kaplan–Meier analysis and a Cox regression model, whereas baseline characteristics and treatment details were collected for competing-risk regression of the association with LP and DM using the Fine–Gray model.

          Results

          A median BED 10 of 67.1 Gy resulted in a disease control rate of 87.7%, and the median OS was 11.8 months after a median follow-up of 32.1 months. The 1-year OS rate, cumulative incidences of LP, and DM were 49.2%, 38.5%, and 62.9%, respectively. Multivariate analyses showed that pre-RT NLR ≥3.5 (adjusted hazard ratio [HR] = 8.245, p < 0.001), CA19-9 reduction rate ≥50% (adjusted HR = 0.261, p = 0.005), RT without concurrent chemoradiotherapy (adjusted HR = 5.903, p = 0.004), and administration of chemotherapy after RT (adjusted HR = 0.207, p = 0.03) were independent prognostic factors for OS. Positive lymph nodal metastases (adjusted subdistribution HR [sHR] = 3.712, p = 0.003) and higher tumor reduction after RT (adjusted sHR = 0.922, p < 0.001) were significant prognostic factors for LP, whereas BED 10 ≥ 67.1 Gy (adjusted sHR = 0.297, p = 0.002), CA19-9 reduction rate ≥50% (adjusted sHR = 0.334, p = 0.023), and RT alone (adjusted sHR = 2.633, p = 0.047) were significant prognostic factors for DM.

          Conclusion

          Our results indicate that pre-RT NLR and post-RT monitoring of CA19-9 and tumor size reduction can help identify whether patients belong to the good or poor prognostic group of LAPC. The incorporation of new systemic treatments during and after a higher BED 10 RT dose for LAPC patients is warranted.

          Related collections

          Most cited references47

          • 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: not found
            • Article: not found

            A Proportional Hazards Model for the Subdistribution of a Competing Risk

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

              Regression Models and Life-Tables

              D R Cox (1972)
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                06 January 2022
                2021
                : 11
                : 730646
                Affiliations
                [1] 1 Division of Radiation Oncology, Department of Oncology, National Taiwan University Hospital , Taipei, Taiwan
                [2] 2 Cancer Research Center, College of Medicine, National Taiwan University , Taipei, Taiwan
                [3] 3 Graduate Institute of Oncology, College of Medicine, National Taiwan University , Taipei, Taiwan
                [4] 4 Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University , Taipei, Taiwan
                [5] 5 Department of Radiology, National Taiwan University Hospital, College of Medicine, National Taiwan University , Taipei, Taiwan
                [6] 6 Department of Radiation Oncology, National Taiwan University Cancer Center, College of Medicine, National Taiwan University , Taipei, Taiwan
                [7] 7 Division of Medical Oncology, Department of Oncology, National Taiwan University Hospital , Taipei, Taiwan
                [8] 8 Department of Surgery, National Taiwan University Hospital , Taipei, Taiwan
                Author notes

                Edited by: James Chow, University of Toronto, Canada

                Reviewed by: Jian-Guo Zhou, Zunyi Medical University, China; Carla Hajj, Memorial Sloan Kettering Cancer Center, United States

                *Correspondence: Sung-Hsin Kuo, shkuo101@ 123456ntu.edu.tw

                This article was submitted to Radiation Oncology, a section of the journal Frontiers in Oncology

                Article
                10.3389/fonc.2021.730646
                8773247
                35070957
                67b50118-b9df-49ed-a3d9-f23eb448ca9b
                Copyright © 2022 Chen, Tsai, Cheng, Wang, Yang, Tien and Kuo

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 25 June 2021
                : 08 December 2021
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 49, Pages: 1, Words: 6020
                Funding
                Funded by: Ministry of Science and Technology , doi 10.13039/501100003711;
                Funded by: National Taiwan University Hospital , doi 10.13039/501100005762;
                Categories
                Oncology
                Original Research

                Oncology & Radiotherapy
                pancreatic cancer,radiotherapy,competing risk,survival,risk factors
                Oncology & Radiotherapy
                pancreatic cancer, radiotherapy, competing risk, survival, risk factors

                Comments

                Comment on this article