Derek Grose1, David S Morrison2, Graham Devereux3, Richard Jones4, Dave Sharma5, Colin Selby6, Kirsty Docherty5, David McIntosh4, Marianne Nicolson7, Donald C McMillan8, Robert Milroy9. 1. Beatson Oncology Centre, 1053 Great Western Road, Glasgow G12 0YN, UK. Electronic address: derek_grose@hotmail.com. 2. Department of Public Health, University of Glasgow, Glasgow, UK. 3. University of Aberdeen, Aberdeen, UK. 4. Beatson Oncology Centre, 1053 Great Western Road, Glasgow G12 0YN, UK. 5. Inverclyde Royal Hospital, Inverclyde, UK. 6. Queen Margaret Hospital, Dunfermline, UK. 7. Aberdeen Royal Infirmary, Aberdeen, UK. 8. University of Glasgow, Glasgow, UK. 9. Glasgow Royal Infirmary, Glasgow, UK.
Abstract
BACKGROUND: Survival from lung cancer remains poor in Scotland, UK. It is believed that comorbidity may play an important role in this. The goal of this study was to determine the value of a novel comorbidity scoring system (SCSS) and to compare it with the already established Charlson Comorbidity Index and the modified Glasgow Prognostic Score (mGPS). We also wished to explore the relationship between comorbidity, mGPS and Performance Status (PS). In addition we investigated a number of standard prognostic markers and demographics. This study aimed to determine which of these factors most accurately predicted survival. METHODS: Between 2005 and 2008 all newly diagnosed lung cancer patients coming through the Multi-Disciplinary Teams (MDTs) in four Scottish Centres were included in the study. Patient demographics, World Health Organization/Eastern Cooperative Oncology Group performance status, clinico-pathological features, mGPS, comorbidity and proposed primary treatment modality were recorded. Univariate survival analysis was carried out using Kaplan-Meier method and the log rank test. RESULTS: This large unselected population based cohort study of lung cancer patients has demonstrated that a number of important factors have significant impact in terms of survival. It has gone further by showing that the factors which influence survival are different, depending upon the stage of cancer at diagnosis and the potential treatment strategy. The novel comorbidity scoring system, the SCSS, has compared very favourably with the more established CCI. CONCLUSION: This study has identified that a variety of factors are independent prognostic determinants of outcome in lung cancer. There appear to be clear differences between the early and late stage groups.
BACKGROUND: Survival from lung cancer remains poor in Scotland, UK. It is believed that comorbidity may play an important role in this. The goal of this study was to determine the value of a novel comorbidity scoring system (SCSS) and to compare it with the already established Charlson Comorbidity Index and the modified Glasgow Prognostic Score (mGPS). We also wished to explore the relationship between comorbidity, mGPS and Performance Status (PS). In addition we investigated a number of standard prognostic markers and demographics. This study aimed to determine which of these factors most accurately predicted survival. METHODS: Between 2005 and 2008 all newly diagnosed lung cancerpatients coming through the Multi-Disciplinary Teams (MDTs) in four Scottish Centres were included in the study. Patient demographics, World Health Organization/Eastern Cooperative Oncology Group performance status, clinico-pathological features, mGPS, comorbidity and proposed primary treatment modality were recorded. Univariate survival analysis was carried out using Kaplan-Meier method and the log rank test. RESULTS: This large unselected population based cohort study of lung cancerpatients has demonstrated that a number of important factors have significant impact in terms of survival. It has gone further by showing that the factors which influence survival are different, depending upon the stage of cancer at diagnosis and the potential treatment strategy. The novel comorbidity scoring system, the SCSS, has compared very favourably with the more established CCI. CONCLUSION: This study has identified that a variety of factors are independent prognostic determinants of outcome in lung cancer. There appear to be clear differences between the early and late stage groups.
Authors: Kristof Cuppens; Christel Oyen; Aurélie Derweduwen; Anouck Ottevaere; Walter Sermeus; Johan Vansteenkiste Journal: Support Care Cancer Date: 2016-01-27 Impact factor: 3.603
Authors: Denise Bernhardt; Sophie Aufderstrasse; Laila König; Sebastian Adeberg; Farastuk Bozorgmehr; Petros Christopoulos; Rami A El Shafie; Juliane Hörner-Rieber; Jutta Kappes; Michael Thomas; Felix Herth; Martin Steins; Jürgen Debus; Stefan Rieken Journal: Cancer Manag Res Date: 2018-11-30 Impact factor: 3.989
Authors: Anna Rich; David Baldwin; Inmaculada Alfageme; Paul Beckett; Thierry Berghmans; Stephen Brincat; Otto Burghuber; Alexandru Corlateanu; Tanja Cufer; Ronald Damhuis; Edvardas Danila; Joanna Domagala-Kulawik; Stefano Elia; Mina Gaga; Tuncay Goksel; Bogdan Grigoriu; Gunnar Hillerdal; Rudolf Maria Huber; Erik Jakobsen; Steinn Jonsson; Dragana Jovanovic; Elena Kavcova; Assia Konsoulova; Tanel Laisaar; Riitta Makitaro; Bakir Mehic; Robert Milroy; Judit Moldvay; Ross Morgan; Milda Nanushi; Marianne Paesmans; Paul Martin Putora; Miroslav Samarzija; Arnaud Scherpereel; Marc Schlesser; Jean-Paul Sculier; Jana Skrickova; Renato Sotto-Mayor; Trond-Eirik Strand; Paul Van Schil; Torsten-Gerriet Blum Journal: BMC Cancer Date: 2018-11-20 Impact factor: 4.430