e-Poster Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2020

Deriving stage at diagnosis from multiple clinical and population-based sources: Non-small cell lung cancer in Queensland (#249)

Morgan Windsor 1 , Margot Lehman 1 , Jasotha Sanmugarajah 1 , Theresa Negrello 2 , Nancy Tran 2 , Tracey Guan 2 , Nathan Dunn 2 , Danica Cossio 2 , Shoni Philpot 2 , David E Theile 3
  1. Cancer Control Safety and Quality Partnership Lung Sub-committee, Woolloongabba, Queensland, Australia
  2. Cancer Alliance Queensland, Woolloongabba, Queensland, Australia
  3. Cancer Control Safety and Quality Partnership, Woolloongabba, Queensland, Australia


Population-based staging data have not previously been reported in lung cancer studies in Australia. We developed the first statewide dataset to include diagnosis, staging, treatment, and survival for non-small cell lung cancer (NSCLC) diagnoses for 2011-2016 in Queensland (N=10,958).


The Queensland Oncology Repository collates and matches patient-level administrative and clinical data from the Queensland Cancer Register (QCR), together with public and private hospital admissions, pathology, radiology, treatment, MDT, and mortality data.

We derived an overall stage category per tumour using a hierarchical approach that prioritised information deemed as best quality, incorporating rules from the AJCC Cancer Staging Manual (7th edition).

For cases where some TNM data was received, a series of registry-derived staging rules were developed to impute missing data. Further, a tumour was assigned to stage IV where admitted patient data or the QCR recorded distant metastasis, minimising missing information.

In collaboration with our established Lung Cancer Quality and Safety Committee, and with a literature review, survival curves and sociodemographic and clinical characteristics according to stage were examined and discussed.


Just under 1 in 5 (17%) patients were diagnosed at stage I, with 7.7% at stage II, 14% at stage III, and 46% at stage IV. Stage was unknown for 16% of patients. This patient group were older, had a higher comorbidity burden, and were less likely to receive anti-cancer treatment compared to patients with a known stage.

Survival curves compare favourably to other jurisdictions, particularly for early-stage disease. The proportion of cases with an unknown stage was lower from 2014-2016 compared to 2011-2013, demonstrating the reporting of stage data may be improving.


We show it is possible to derive stage using registry rules based on data from multiple population-based sources to create statewide staging information for lung cancer in Queensland.