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Purpose Using population-based data for women diagnosed with stage I-III breast cancer, our aim was to examine the impact of time to treatment completion on survival and to identify factors associated with treatment delay. Methods This retrospective study used clinical and treatment data from the Queensland Oncology Repository. Time from diagnosis to completing surgery, chemotherapy and radiation therapy identified a cut-off of 37 weeks as the optimal threshold for completing treatment. Logistic regression was used to identify factors associated with the likelihood of completing treatment > 37 weeks. Overall (OS) and breast cancer-specific survival (BCSS) were examined using Cox proportional hazards models. Results Of 8279 women with stage I-III breast cancer, 31.9% completed treatment > 37 weeks. Apart from several clinical factors, being Indigenous (p = 0.002), living in a disadvantaged area (p = 0.003) and receiving ≥ two treatment modalities within the public sector (p 37 weeks. The risk of death from any cause was about 40% higher for women whose treatment went beyond 37 weeks (HR 1.37, 95%CI 1.16–1.61), a similar result was observed for BCSS. Using the surgery + chemotherapy + radiation pathway, a delay of > 6.9 weeks from surgery to starting chemotherapy was significantly associated with poorer survival (p = 0.001). Conclusions Several sociodemographic and system-related factors were associated with a greater likelihood of treatment completion > 37 weeks. We are proposing a key performance indicator for the management of early breast cancer where a facility should have > 90% of patients with a time from surgery to adjuvant chemotherapy

Background Registry-derived stage (RD-Stage) provides a mechanism to capture cancer stage at diagnosis from routinely captured data available to population-based cancer registries (PBCRs). In 2021, a project was undertaken to develop business rules to capture RD-Stage for endometrial cancer, understand current capacity to capture this information at a national level, and assess how it compares with stage recorded in clinical notes at diagnosis by clinicians. Methodology Business rules for deriving RD-stage (Endometrial carcinoma) were developed using AJCC Cancer Staging Manual 8th edition and endorsed by a tumour-specific Expert Working group comprising cancer specialists responsible for delivering cancer care and PBCR epidemiologists and medical coders. Baseline completeness of data fields required to calculate RD-Stage, and an overall proportion of cases for whom an RD stage could be assigned was assessed across each Australian jurisdiction. A validation study was undertaken in one jurisdiction to compare RD-Stage (Endometrial cancer) calculated by the Victorian Cancer Registry (VCR) with clinical stage recorded in cases diagnosed in 2018-2020 in the National Gynae-Oncology Registry (NGOR). Results The level of completeness of data to enable RD-Stage (Endometrial carcinoma) to be calculated across jurisdictions ranged from 0 to 89%. Three jurisdictions captured degree of spread of cancer only (instead of TNM data) and therefore captured no data which would enable RD-Stage to be calculated. The RD-Stage (Endometrial carcinoma) validation study found that RD-Stage could not be derived for 64/485 (13%) cases in the VCR and was not captured for 44/485 (9%) cases in NGOR. There was concordance at stage level (I, II, III, IV) in 393/410 (96%) of cases (95.8%, Kendall’s coefficient=0.95). Conclusion A lack of consistency in data captured by, and data sources reporting to, PBCRs meant that it was not possible to provide an accurate national baseline of endometrial carcinoma stage at diagnosis. In a sample of Victorian cases, there was very good concordance between RD-Stage (Endometrial carcinoma) and that recorded by clinicians in medical records and captured by NGOR. However, for 10% of cases RD-Stage could not be calculated because data was not available. RD-Stage provides a useful tool to be used for population epidemiological purposes.

Purpose: Cancer remains the most common cause of disease-related death among young people and carries a significant burden. In the absence of prior state-based Australian epidemiological studies, t...

Optimal management of regional lymph nodes for thin cutaneous melanoma is uncertain. We evaluated regional lymph node involvement and 5-year melanoma-specific survival (MSS) in patients with thin (≤1 mm) primary melanoma.Patients with a melanoma, American Joint Committee on Cancer Staging 8th Edition pT1a (0.8 mm) or pT1b (ulceration; and/or 0.8-1.0 mm), diagnosed during 2001-2015 were identified from the Queensland Oncology Repository. We extracted demographic, pathology and clinical details, including sentinel lymph node biopsy (SLNB), regional nodal dissection and nodal recurrence. Poisson regression was used to assess recurrence risk in patients who did not undergo SLNB. The 5-year MSS was calculated using the Kaplan-Maier method with Cox regression to compare survival outcomes according to SLNB performance.Of the 27 824 eligible patients, 240 (0.9%) underwent SLNB. One hundred and seventy-eight patients (0.6%) without SLNB had nodal recurrence. Of the 4848 patients with a pT1b lesion, 166 (3.4%) had SLNB with 12 (7.2%) positive; of the remainder, 99 (2.1%) had clinical recurrence. Risk of recurrence was higher in males, nodular subtype and T1b lesions and lower if patients were aged60 years. The 5-year MSS was similar for observed and SLNB cohorts (99.66% versus 98.92%) but worse for T1b lesions (98.90%) and clinical nodal recurrence (66.89%).Overall prognosis for T1 melanoma is excellent with nodal involvement being rare. However, the American Joint Committee on Cancer 8th Edition T1b melanoma correlates with significantly worse 5-year MSS and increased regional nodal recurrence (notably for 0.8-1.0 mm lesions with ulceration). Further characterization of high-risk groups for nodal positivity that impacts patient outcome is needed for the pT1 melanoma cohort.

10566 Background: Disparity in outcome for different cancer groups exist particularly for indigenous and poor socioeconomic background. Patient and treatment data on a population basis was examined. Methods: Population data for the state of Queensland, Australia (population 5.2M) collected by Cancer Alliance Queensland as part of government cancer registry roles plus additional linked data available as a gazetted quality assurance committee was examined to find patients with early breast cancer treated with surgery, chemotherapy (CT) and radiotherapy (RT) between 2005-2015. Results: A cohort of 8279 women received treatment with 89.3% having the surgery, CT, RT sequence. Time to completement threshold was 37 weeks using empirical cutpoint estimation in Stata. Overall survival (OS) was 94% at 5 years if < 37 weeks versus 88.5% if not. (p < 0.001). Multivariate analysis of socioeconomic and clinical characteristics for survival was also significant for increasing age, indigenous status, socioeconomic disadvantage, multiple co morbidities and advancing disease stage. Private hospital cases had a better outcome. When delay is analysed between treatments, only time to CT from surgery > 9.5 weeks was significant for OS (HR 1.42 p < 0.001). Indigenous status, socioeconomic status and private facility no longer were significant. Multiple co morbidities and advanced stage were still significantly associated with poorer survival. Funnel plots of treatment centre show the association with public hospital treatment and lower volume centre with delay. Conclusions: This data is retrospective so can inform local service evaluation but implementation of a KPI for delay to adjuvant chemotherapy of 9.5 weeks can provide real time targets for patient care. We measured delay in the recent 5 years (before survival available) which shows consistent delays and it will included as a reporting function of MDT management software. Whilst the increased use of neoadjuvant CT will assist, systematic reporting of this KPI has potential to remove treatment biases for indigenous and lower socioeconomic patients. More recent data will be available for presentation.

Aim: To determine whether lung cancer radiation therapy waiting times in Queensland public hospitals are associated with distance of residence from the nearest treatment facility. Methods: Retrospective analysis of radiation therapy waiting times of 1535 Queensland residents who were diagnosed with lung cancer from 2000 to 2004 and received radiation therapy as initial treatment at a public hospital. The effect of distance of residence from treatment centre on median waiting time was analysed by quantile regression controlling for sex, age, lung cancer histology, stage and therapeutic intent. Results: The median waiting time from diagnosis to start of radiation therapy was 33 days for all patients. There was no significant difference (P = 0.141) in median waiting times in relation to distance of residence from a treatment centre. However, in most patients, waiting times were significantly longer than recommended by the Royal Australian and New Zealand College of Radiologists. Curative patients waited longer than palliative patients, while patients with earlier stage cancer waited longer than those with more advanced disease. Conclusion: Waiting times for radiation therapy among lung cancer patients in Queensland was not associated with distance from place of residence to the nearest public treatment facility. However, delays overall are excessive and are likely to worsen unless radiation treatment capabilities are enhanced to keep pace with population growth in Queensland.