Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy.

AIMS: Delineation variations and organ motion produce difficult-to-quantify uncertainties in planned radiation doses to targets and organs at risk. Similar to manual contouring, most automatic segmentation tools generate single delineations per structure; however, this does not indicate the range of clinically acceptable delineations. This study develops a method to generate a range of automatic cardiac structure segmentations, incorporating motion and delineation uncertainty, and evaluates the dosimetric impact in lung cancer. MATERIALS AND METHODS: Eighteen cardiac structures were delineated using a locally developed auto-segmentation tool. It was applied to lung cancer planning CTs for 27 curative (planned dose ≥50 Gy) cases, and delineation variations were estimated by using ten mapping-atlases to provide separate substructure segmentations. Motion-related cardiac segmentation variations were estimated by auto-contouring structures on ten respiratory phases for 9/27 cases that had 4D-planning CTs. Dose volume histograms (DVHs) incorporating these variations were generated for comparison. RESULTS: Variations in mean doses (Dmean), defined as the range in values across ten feasible auto-segmentations, were calculated for each cardiac substructure. Over the study cohort the median variations for delineation uncertainty and motion were 2.20-11.09 Gy and 0.72-4.06 Gy, respectively. As relative values, variations in Dmean were between 18.7%-65.3% and 7.8%-32.5% for delineation uncertainty and motion, respectively. Doses vary depending on the individual planned dose distribution, not simply on segmentation differences, with larger dose variations to cardiac structures lying within areas of steep dose gradient. CONCLUSION: Radiotherapy dose uncertainties from delineation variations and respiratory-related heart motion were quantified using a cardiac substructure automatic segmentation tool. This predicts the 'dose range' where doses to structures are most likely to fall, rather than single DVH curves. This enables consideration of these uncertainties in cardiotoxicity research and for future plan optimisation. The tool was designed for cardiac structures, but similar methods are potentially applicable to other OARs.

Federated Learning Survival Model and Potential Radiotherapy Decision Support Impact Assessment for Non-small Cell Lung Cancer Using Real-World Data.

AIMS: The objective of this study was to develop a two-year overall survival model for inoperable stage I-III non-small cell lung cancer (NSCLC) patients using routine radiation oncology data over a federated (distributed) learning network and evaluate the potential of decision support for curative versus palliative radiotherapy. METHODS: A federated infrastructure of data extraction, de-identification, standardisation, image analysis, and modelling was installed for seven clinics to obtain clinical and imaging features and survival information for patients treated in 2011-2019. A logistic regression model was trained for the 2011-2016 curative patient cohort and validated for the 2017-2019 cohort. Features were selected with univariate and model-based analysis and optimised using bootstrapping. System performance was assessed by the receiver operating characteristic (ROC) and corresponding area under curve (AUC), C-index, calibration metrics and Kaplan-Meier survival curves, with risk groups defined by model probability quartiles. Decision support was evaluated using a case-control analysis using propensity matching between treatment groups. RESULTS: 1655 patient datasets were included. The overall model AUC was 0.68. Fifty-eight percent of patients treated with palliative radiotherapy had a low-to-moderate risk prediction according to the model, with survival times not significantly different (p = 0.87 and 0.061) from patients treated with curative radiotherapy classified as high-risk by the model. When survival was simulated by risk group and model-indicated treatment, there was an estimated 11% increase in survival rate at two years (p < 0.01). CONCLUSION: Federated learning over multiple institution data can be used to develop and validate decision support systems for lung cancer while quantifying the potential impact of their use in practice. This paves the way for personalised medicine, where decisions can be based more closely on individual patient details from routine care.

Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy.

BACKGROUND AND PURPOSE: Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segmentation tool for automatic delineation of cardiac structures and subsequent dose evaluation, with potential application in clinical settings and large-scale radiation-related cardiotoxicity studies. MATERIALS AND METHODS: A recently developed hybrid method for automatic segmentation of 18 cardiac structures, combining deep learning, multi-atlas mapping and geometric segmentation of small challenging substructures, was independently validated on 30 lung cancer cases. These included anatomical and imaging variations, such as tumour abutting heart, lung collapse and metal artefacts. Automatic segmentations were compared with manual contours of the 18 structures using quantitative metrics, including Dice similarity coefficient (DSC), mean distance to agreement (MDA) and dose comparisons. RESULTS: A comparison of manual and automatic contours across all cases showed a median DSC of 0.75-0.93 and a median MDA of 2.09-3.34 mm for whole heart and chambers. The median MDA for great vessels, coronary arteries, cardiac valves, sinoatrial and atrioventricular conduction nodes was 3.01-8.54 mm. For the 27 cases treated with curative intent (planned target volume dose ≥50 Gy), the median dose difference was -1.12 to 0.57 Gy (absolute difference of 1.13-3.25%) for the mean dose to heart and chambers; and -2.25 to 4.45 Gy (absolute difference of 0.94-6.79%) for the mean dose to substructures. CONCLUSION: The novel hybrid automatic segmentation tool reported high accuracy and consistency over a validation set with challenging anatomical and imaging variations. This has promising applications in substructure dose calculations of large-scale datasets and for future studies on long-term cardiac toxicity.

Patterns of palliative radiotherapy fractionation for brain metastases patients in New South Wales, Australia.

BACKGROUND AND PURPOSE: There is a paucity of studies examining variation in the use of palliative radiation therapy (RT) fractionation for brain metastases. The aim of this study is to assess variation in palliative RT fractionation given for brain metastases in New South Wales (NSW), Australia, and identify factors associated with variation. MATERIALS AND METHODS: This is a population-based cohort of patients who received whole brain RT (WBRT) for brain metastases (2009-2014), as captured in the NSW Central Cancer Registry. A logistic regression model was used to identify factors associated with fractionation type. RESULTS: Of the 2,698 patients that received WBRT, 1,389 courses (51%) were < 6 fractions, 1,050 courses (39%) were 6-10 fractions, and 259 courses (10%) were > 10 fractions. Older patients were more likely to be treated with shorter courses (P < 0.0001). Patients with primary lung cancers were more likely to receive shorter courses compared with other primary cancers (P < 0.0001). Patients without surgical excision were more likely to receive < 6 fractions compared to those who underwent surgical excision. Shorter courses were more likely to be delivered to patients with the most disadvantaged socioeconomic status (SES) compared with patients with the least disadvantaged SES (P < 0.0001). There were significant fluctuations in the proportion of courses using lower number of fractions over time from 2009 to 2014, but no apparent trend (P = 0.02). There was wide variation in the proportion of shorter courses across residence local health districts, ranging from 24% to 69% for < 6 fractions, 21% to 72% for 6-10 fractions, and 4% to 20% for > 10 fractions (P < 0.0001). CONCLUSION: This study has identified significant unwarranted variations in fractionation for WBRT in NSW. Accelerating the uptake of shorter fractionation regimens, if warranted through evidence, should be prioritised to enhance evidence-based care.

Patterns of use of palliative radiotherapy fractionation for bone metastases and 30-day mortality.

BACKGROUND AND PURPOSE: Adoption of single-fraction radiation therapy (SFRT) has not been universal in the palliative treatment of bone metastases, despite evidence supporting its safety and efficacy. The aim of this study was to assess SFRT use for bone metastases in New South Wales (NSW), Australia, and the rate of 30-day mortality (30DM). MATERIALS AND METHODS: This is a population-based cohort of patients who received palliative radiation therapy (RT) for bone metastases (2009-2014), as captured in the NSW Central Cancer Registry. A logistic regression model was used to identify factors associated with fractionation type. The proportion of patients dying within 30-days from treatment start date was calculated. RESULTS: Of the 14,602 courses of palliative RT delivered for bone metastases, 30% were SFRT. SFRT was more likely to be delivered to older patients: ≥80 years (34%) versus < 60 years (28%). Patients with lower socioeconomic status (SES) (35%) were more likely to receive SFRT compared with higher SES (25%). SFRT delivered to patients from outer regional area of residence (34%) were higher compared to those from the major city (29%). The proportion of SFRT delivered to patients with comorbidities ≥2 (34%) was higher than patients with no comorbidity (29%). SFRT was associated with higher 30DM of 21% compared with 11% for multi-fraction RT (MFRT). CONCLUSION: SFRT is underused for the treatment of bone metastases in NSW. This is an impetus to develop tools making SFRT obligatory in this setting unless there is good justification not to.

The population benefit of evidence-based radiotherapy: 5-Year local control and overall survival benefits.

BACKGROUND: To describe the population benefit of radiotherapy in a high-income setting if evidence-based guidelines were routinely followed. METHODS: Australian decision tree models were utilized. Radiotherapy alone (RT) benefit was defined as the absolute proportional benefit of radiotherapy compared with no treatment for radical indications, and of radiotherapy over surgery alone for adjuvant indications. Chemoradiotherapy (CRT) benefit was the absolute incremental benefit of concurrent chemoradiotherapy over RT. Five-year local control (LC) and overall survival (OS) benefits were measured. Citation databases were systematically queried for benefit data. Meta-analysis and sensitivity analysis were performed. FINDINGS: 48% of all cancer patients have indications for radiotherapy, 34% curative and 14% palliative. RT provides 5-year LC benefit in 10.4% of all cancer patients (95% Confidence Interval 9.3, 11.8) and 5-year OS benefit in 2.4% (2.1, 2.7). CRT provides 5-year LC benefit in an additional 0.6% of all cancer patients (0.5, 0.6), and 5-year OS benefit for an additional 0.3% (0.2, 0.4). RT benefit was greatest for head and neck (LC 32%, OS 16%), and cervix (LC 33%, OS 18%). CRT LC benefit was greatest for rectum (6%) and OS for cervix (3%) and brain (3%). Sensitivity analysis confirmed a robust model. INTERPRETATION: Radiotherapy provides significant 5-year LC and OS benefits as part of evidence-based cancer care. CRT provides modest additional benefits.

The Benefits of Providing External Beam Radiotherapy in Low- and Middle-income Countries.

More than half of all cancer diagnoses worldwide occur in low- and middle-income countries (LMICs) and the incidence is projected to rise substantially within the next 20 years. Radiotherapy is a vital, cost-effective treatment for cancer; yet there is currently a huge deficit in radiotherapy services within these countries. The aim of this study was to estimate the potential outcome benefits if external beam radiotherapy was provided to all patients requiring such treatment in LMICs, according to the current evidence-based guidelines. Projected estimates of these benefits were calculated to 2035, obtained by applying the previously published Collaboration for Cancer Outcomes, Research and Evaluation (CCORE) demand and outcome benefit estimates to cancer incidence and projection data from the GLOBOCAN 2012 data. The estimated optimal radiotherapy utilisation rate for all LMICs was 50%. There were about 4.0 million cancer patients in LMICs who required radiotherapy in 2012. This number is projected to increase by 78% by 2035, a far steeper increase than the 38% increase expected in high-income countries. National radiotherapy benefits varied widely, and were influenced by case mix. The 5 year population local control and survival benefits for all LMICs, if radiotherapy was delivered according to guidelines, were estimated to be 9.6% and 4.4%, respectively, compared with no radiotherapy use. This equates to about 1.3 million patients who would derive a local control benefit in 2035, whereas over 615 000 patients would derive a survival benefit if the demand for radiotherapy in LMICs was met. The potential outcome benefits were found to be higher in LMICs. These results further highlight the urgent need to reduce the gap between the supply of, and demand for, radiotherapy in LMICs. We must attempt to address this 'silent crisis' as a matter of priority and the approach must consider the complex societal challenges unique to LMICs.

A Population-based Model of Local Control and Survival Benefit of Radiotherapy for Lung Cancer.

AIMS: To estimate the population-based locoregional control and overall survival benefits of radiotherapy for lung cancer if the whole population were treated according to evidence-based guidelines. These estimates were based on a published radiotherapy utilisation (RTU) model that has been used to estimate the demand and planning of radiotherapy services nationally and internationally. MATERIALS AND METHODS: The lung cancer RTU model was extended to incorporate an estimate of benefits of radiotherapy alone, and of radiotherapy in conjunction with concurrent chemotherapy (CRT). Benefits were defined as the proportional gains in locoregional control and overall survival from radiotherapy over no radiotherapy for radical indications, and from postoperative radiotherapy over surgery alone for adjuvant indications. A literature review (1990-2015) was conducted to identify benefit estimates of individual radiotherapy indications and summed to estimate the population-based gains for these outcomes. Model robustness was tested through univariate and multivariate sensitivity analyses. RESULTS: If evidence-based radiotherapy recommendations are followed for the whole lung cancer population, the model estimated that radiotherapy alone would result in a gain of 8.3% (95% confidence interval 7.4-9.2%) in 5 year locoregional control, 11.4% (10.8-12.0%) in 2 year overall survival and 4.0% (3.6-4.4%) in 5 year overall survival. For the use of CRT over radiotherapy alone, estimated benefits would be: locoregional control 1.7% (0.8-2.4%), 2 year overall survival 1.7% (0.5-2.8%) and 5 year overall survival 1.2% (0.7-1.9%). CONCLUSIONS: The model provided estimates of radiotherapy benefit that could be achieved if treatment guidelines are followed for all cancer patients. These can be used as a benchmark so that the effects of a shortfall in the utilisation of radiotherapy can be better understood and addressed. The model can be adapted to other populations with known epidemiological parameters to ensure the planning of equitable radiotherapy services.

The population benefit of radiotherapy for cervical cancer: local control and survival estimates for optimally utilized radiotherapy and chemoradiation.

PURPOSE: Population benefits of radiotherapy if evidence-based guidelines were routinely followed across the entire population are largely unknown. The aim of this study was to investigate population-based benefits for cervical cancer. METHODS: Overall survival (OS) and local control (LC) benefits were investigated. XRT benefit was defined as the absolute benefit of radiotherapy, over no treatment, for radical indications and defined as the benefit of adjuvant radiation over surgery alone for adjuvant indications. The concurrent chemoradiation (CRT) benefit was the incremental benefit of CRT over XRT. Australian population benefits were modeled using decision trees. Citation databases were systematically queried. Meta-analysis was performed if multiple sources of the same evidence level existed. Robustness of the model assumptions was tested through sensitivity analysis. RESULTS: 53% of all cervix patients had adjuvant or curative radiotherapy indications. 96% were for CRT. The estimated 5-year absolute benefits of optimally utilized radiotherapy alone were: LC: 31% (95% Confidence Interval 29%, 34%), OS: 17% (15%, 18%). These were over and above the contribution of other modalities to outcomes. The incremental 5-year absolute benefits of CRT were: LC 4% (2%, 5%), OS 3% (1%, 5%). In sensitivity analysis, the model was robust. CONCLUSIONS: Optimally utilized radiotherapy provides substantial population OS and LC benefits for cervical cancer. Chemoradiation provides a modest population benefit over XRT. The population-based model was robust.

Evidence-based estimates of the demand for radiotherapy.

There are different methods that may be used to estimate the future demand for radiotherapy services in a population ranging from expert opinion through to complex modelling techniques. This manuscript describes the use of evidence-based treatment guidelines to determine indications for radiotherapy. It also uses epidemiological data to estimate the proportion of the population who have attributes that suggest a benefit from radiotherapy in order to calculate the overall proportion of a population of new cases of cancer who appropriately could be recommended to undergo radiotherapy. Evidence-based methods are transparent and adaptable to different populations but require extensive information about the indications for radiotherapy and the proportion of cancer cases with those indications in the population. In 2003 this method produced an estimate that 52.4% of patients with a registered cancer-type had an indication for radiotherapy. The model was updated in 2012 because of changes in cancer incidence, stage distributions and indications for radiotherapy. The new estimate of the optimal radiotherapy utilisation rate was 48.3%. The decrease was due to changes in the relative frequency of cancer types and some changes in indications for radiotherapy. Actual rates of radiotherapy utilisation in most populations still fall well below this benchmark.

Patterns of retreatment by radiotherapy.

AIMS: To describe patterns of treatment for those who receive more than one episode of megavoltage radiotherapy (retreatment) by cancer type for better service planning and benchmarking. MATERIALS AND METHODS: Institutional databases of all patients who received their first megavoltage radiotherapy for any type of cancer at the Liverpool and Macarthur Cancer Therapy Centres (LM), New South Wales, Australia, Royal Brisbane and Women's Hospital (RBWH), Queensland, Australia and Radiotherapeutic Institution Friesland (RIF), Leeuwarden, the Netherlands, over the period 1991-2009 were examined. Radiotherapy retreatment was defined as any radiotherapy episode, to any body site, after an initial episode of radiotherapy, for the same cancer diagnosis. The total retreatment rate was defined as the number of retreatment episodes of radiotherapy divided by the number of cases in the cohort. RESULTS: In total, 62,270 patients (RBWH 38581, LM 9654, RIF 14035) received 77,762 episodes of radiotherapy, giving a total retreatment rate of 0.25; 52,351 patients (84%) received only one episode of treatment and 9919 (16%) received two or more episodes of treatment. Overall retreatment rates for LM, RBWH and RIF were 0.24, 0.25 and 0.26, respectively. For the five most common cancer types treated, the median time between treatment episodes was longest for breast cancer (11.3 months), then head and neck cancer (9.7 months), colorectal cancer (7.2 months), prostate cancer (4.4 months) and lung cancer (4.1 months). Ninety-one per cent of all fractions were delivered in the first episode of treatment. CONCLUSIONS: The retreatment rate was very similar between the three facilities, suggesting agreement about the indications for retreatment.

A review of the management of ductal carcinoma in situ following breast conserving surgery.

Ductal carcinoma in situ (DCIS) is a heterogeneous, pre-malignant disease accounting for 10-20% of all new breast tumours. Evidence shows a statistically significant local control benefit for adjuvant radiotherapy (RT) following breast conserving surgery (BCS) for all patients. The baseline recurrence risk of individual patients varies according to clinical-pathological criteria and in selected patients, omission of RT may be considered, following a discussion with the patient. The role of adjuvant endocrine therapy remains uncertain. Ongoing studies are attempting to define subgroups of patients who are at sufficiently low risk of recurrence that RT may be safely omitted; investigating RT techniques and dose fractionation schedules; and defining the role of endocrine therapy. Future directions in the management of patients with DCIS will include investigation of prognostic and predictive biomarkers to inform individualised therapy tailored to the risk of recurrence.

The potential for an enhanced role for MRI in radiation-therapy treatment planning.

The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors.

A comparison of surgical and radiotherapy breast cancer therapy utilization in Canada (British Columbia), Scotland (Dundee), and Australia (Western Australia) with models of "optimal" therapy.

BACKGROUND: Different jurisdictions report different breast cancer treatment rates. Evidence-based utilization models may be specific to derived populations. We compared predicted optimal with actual radiotherapy utilization in British Columbia, Canada; Dundee, Scotland; and Perth, Western Australia. DESIGN: Data were analyzed for differences in demography, tumor, and treatment. Epidemiological data were fitted to published Australian optimal radiotherapy utilization trees and region-specific optimal treatment rates were calculated. Optimal and actual surgery/radiotherapy rates from 2 population-based and 1 institution-based registries were compared for patients diagnosed with breast cancer between 2000 and 2004, and 2002 for British Columbia. RESULTS: Mastectomy rates differed between British Columbia (40%), Western Australia (44%), and Dundee (47%, p<0.01). Radiotherapy rates differed between British Columbia (60%), Western Australia (52%), and Dundee (49%, p<0.01). Actual radiotherapy utilization rates were lower than optimal estimates. Region-specific optimal utilization rates at diagnosis varied from 57% to 71% for radiotherapy and 62% to 64% when taking into account patient preference. Variation was attributed to local differences in demography and tumor stage. CONCLUSIONS: Actual treatment rates varied, and were associated with patterns of care and guideline differences. Actual radiotherapy rates were lower than optimal rates. Differences between optimal and actual utilization may be due to access shortfalls, and patient preference.

Estimation of an optimal chemotherapy utilisation rate for primary malignant brain tumours: an evidence-based benchmark for cancer care.

AIMS: The optimal chemotherapy utilisation rate can serve as a benchmark to assess the quality of cancer care. The aim of this study was to determine the optimal proportion of patients with primary malignant brain tumours for whom there was evidence that they should receive chemotherapy at least once. MATERIALS AND METHODS: An optimal chemotherapy utilisation tree was constructed using indications for chemotherapy identified from evidence-based treatment guidelines. Data on the proportion of patient and tumour-related attributes for which chemotherapy was indicated were obtained and merged with the treatment indications to calculate an optimal chemotherapy utilisation rate. This optimal rate was compared with reported actual rates of chemotherapy utilisation. RESULTS: Chemotherapy is indicated at least once, either as an initial treatment or at recurrence (in those who have not previously received chemotherapy), in 72% of all patients with primary malignant brain tumours. No recent published data on actual chemotherapy utilisation rates were identified for comparison with the optimal rate. CONCLUSION: The optimal chemotherapy utilisation rate can serve as an evidence-based benchmark in the planning and evaluation of chemotherapy services for brain cancer. There are no recent published patterns of care studies that report on chemotherapy utilisation rates for primary malignant brain tumours; future research should focus on filling this gap.

Interobserver variability in clinical target volume delineation in tangential breast irradiation: a comparison between radiation oncologists and radiation therapists.

AIMS: The delineation of target volumes has been radiation oncologist led. If radiation therapists were to undertake this task, work processes may be more efficient and the skills set of radiation therapy staff broadened. This study was undertaken to quantify interobserver variability of breast target volumes between radiation oncologists and radiation therapists. MATERIALS AND METHODS: The planning computed tomography datasets of 30 patients undergoing tangential breast radiotherapy were utilised. Four radiation oncologists and four radiation therapists independently contoured the clinical target volume (CTV) of the breast on planning computed tomography using a written protocol. The mean CTV volumes and the mean distance between centres of volume (COV) were determined for both groups to determine intergroup variation. Each of the radiation oncologists' readings in turn has been used as the gold standard and compared with that of the radiation therapists. The concordance index for each patient's CTV was determined relative to the gold standard for each group. A paired t-test was used for statistical comparison between the groups. An intraclass correlation coefficient was calculated to measure the agreement between the radiation oncologist and radiation therapist groups. RESULTS: The mean concordance index was 0.81 for radiation oncologists and 0.84 for radiation therapists. The intraclass correlation coefficient for the mean volume was 0.995 (95% confidence interval 0.981-0.998) between radiation oncologist- and radiation therapist-contoured volumes. The intraclass correlation for the mean difference between radiation oncologists' and radiation therapists' COV was 0.999 (95% confidence interval 0.999-1.000). CONCLUSIONS: Interobserver variability between radiation oncologists and radiation therapists was found to be low. Radiation therapists could potentially assume the role of CTV voluming for breast radiotherapy provided a standardised contouring protocol is in place.

Estimation of an optimal utilisation rate for palliative radiotherapy in newly diagnosed cancer patients.

AIMS: An optimal utilisation rate for palliative radiotherapy in newly diagnosed cancers will be useful in the planning and delivery of cancer services and has not been reported to date. The aim of this study was to estimate the proportion of new cases of cancer that should receive palliative radiotherapy as their first course of radiotherapy at some time during the course of their illness. MATERIALS AND METHODS: A previously developed model depicting indications for radiotherapy was merged with Australian cancer epidemiological data and re-analysed to identify palliative or radical treatment end points. Palliative radiotherapy end points were further divided by treatment site. The optimal palliative radiotherapy utilisation rates were compared with actual radiotherapy utilisation data for newly diagnosed cancers. RESULTS: Fourteen per cent of all new cancer cases should optimally receive palliative radiotherapy as their first course of radiotherapy treatment. Comparisons with actual radiotherapy utilisation rates from New South Wales, Australia, show that for some common cancers, more newly diagnosed patients receive palliative radiotherapy as their first radiotherapy treatment than would be optimally recommended in this model. This suggests that many patients in New South Wales are not currently being referred for curative treatment. CONCLUSION: Palliative radiotherapy is optimally recommended as the first course of radiotherapy in 14% of all newly diagnosed cancers.

No improvement in lung cancer care: the management of lung cancer in 1996 and 2002 in New South Wales.

BACKGROUND: Patterns-of-care studies emphasize significant variation in the management of lung cancer. The aim of the study was to compare the patterns of care for patients diagnosed with lung cancer in 1996 and 2002 within three health areas in New South Wales. METHODS: Treatment data were collected from medical records and treating doctors for the calendar year 1996 and between 1 November 2001 and 31 December 2002. Patients were residents of either south-western Sydney, Hunter or Northern Sydney health areas at the time of diagnosis. chi(2)-tests were used to investigate changes in treatment patterns between the two time periods. An adjusted odds ratio for treatment in 2002 relative to 1996 was calculated using logistic regression. RESULTS: Data were available for 738 and 567 cases in 1996 and 2002, respectively. Cancer-specific therapy was given within 6 months of diagnosis to 62 and 64% of patients, respectively. Adjusting for health area, age, sex, pathology and performance status, the odds ratio (OR) of treatment in 2002 relative to 1996 was 1.03 (95% confidence interval (CI) 0.78-1.35). When stage was included, the odds of treatment in 2002 relative to 1996 for non-small-cell lung cancer (n = 950) was 1.21 (95%CI 0.87-1.68). After adjustment for potential confounders, patients diagnosed with small-cell lung cancer (n = 176) were substantially less likely to receive treatment in 2002 compared with patients diagnosed in 1996 (OR = 0.11; 95%CI 0.04-0.34). CONCLUSION: The odds of receiving treatment in 2002 and 1996 were similar. However, patients diagnosed with small-cell lung cancer in 2002 were significantly less likely to receive treatment. Overall, this study suggests there has been no change in lung cancer care in New South Wales. Further work is required to determine what proportion of persons with lung cancer should receive cancer-specific treatment so that clinical practices can be judged appropriately.