Biomedical subjects

M Lunn

Publications and source records attributed to M Lunn.

7 recordsLinked to original sources

PubMed1999

An Australasian assessment of the basic treatment equivalent model derived from New South Wales data.

The current method of assessment of radiation oncology linear accelerator throughput is either by patients per unit time or fields per unit time. This, however, does not take into consideration the complexity of different treatment techniques or of casemix. A model has been developed in an earlier study, called 'basic treatment equivalent' (BTE), to measure patient throughput of a linear accelerator, which includes consideration of the complexity of treatment techniques. The present study compared the BTE model with the current best measure of patient throughput of fields per hour. All 37 departments in Australia and New Zealand were invited to participate in testing the model, and 36 agreed to participate. The study period for each department was a consecutive 4 weeks between August and December, 1996. The prospective data collected were the total BTE units treated per linear accelerator per day, the total number of patients and fields treated per linear accelerator per day, and the total linear accelerator hours of operation per day excluding calibration time and significant breaks of linear accelerator time such as planned meal breaks. The treatment breaks between consecutive treatment fractions were not excluded from the linear accelerator treatment time. The throughput data for 36 departments (92 linear accelerators) were collected over the 4-week study period. The average throughput for the departments was 10.8 fields per hour and 4.2 patients per hour. The average BTE per department was 5.7 BTE per hour. The average BTE per episode per department was 1.38. The BTE model was found to be a more sensitive measure of productivity compared with fields per hour (P < 0.001). Some treatment techniques were thought to be not well represented by the BTE formula, particularly those techniques where junctions were present. The BTE model is a more sensitive measure than fields per hour and better reflects the variations in complexity in techniques. Despite this result there is further refinement to be performed to make the model even more sensitive.

Data Collection↗

PubMed1999

Refinement of the basic treatment equivalent model to reflect radiotherapy treatment throughput using Australasian data.

A model of radiotherapy linear accelerator throughput has been developed and shown to be a more sensitive measure of throughput than current measures of throughput. The present study aims to develop a more sensitive basic treatment equivalent (BTE) model that still measures linear accelerator throughput and considers some of the shortcomings of the previous model. All radiation oncology departments in Australia and New Zealand were invited to participate. Departments were asked to time with a stopwatch all episodes of radiotherapy treatment over a 4-week period. Data collected for each treatment fraction included treatment intent, tumour site, patient age, Eastern Cooperative Oncology Group (ECOG) performance status, number of fields used, number of wedges used, number of junctions, number of shielding blocks used, whether the treatment was the first fraction, the use of general anaesthesia and whether port films or electronic portal imaging was used. Twenty-six departments of radiation oncology (70%) participated in this trial. A total of 7929 fractions of treatment, administered to 2424 patients, were timed. The factors found to most significantly impact on treatment duration on multivariate analysis were the type of fraction (first fraction was longer than subsequent fractions), type of beam (electrons were quicker than photons, which were quicker than mixed), number of fields, number of shields, number of junctions, number of port films and performance status (ECOG < 2 vs > 2). The age of the patient, number of compensators and the sex of the patient were not significant. The relationships between factors were assessed, and models of measuring linear accelerator throughput which consider complexity corrections were derived. It is possible to show that linear accelerator throughput is poorly measured by just considering numbers of patients or fields treated per unit time; and that other factors that impact on treatment duration must be considered. A more sensitive model of patient throughput is suggested; but even when a large number of factors are considered, some insensitivity still remains in the model.

Australia↗

PubMed1998

Applying k-sample tests to conditional probabilities for competing risks in a clinical trial.

In the presence of competing risks, a full picture of the data can be developed considering the cumulative incidence function for each risk. If one risk type is of particular interest, the conditional probability of failure due to that risk, conditional on no failure due to the remaining competing risks, can be used to compare any number of samples. Kappa-sample tests of significance are derived and extended to stratified test statistics, allowing adjustment to be made for important prognostic factors. The methods are applied to a clinical trial involving patients with advanced breast cancer, where interest focused on progression of disease at old and new sites. They show that estrogen receptor status positive is an important prognostic factor in terms of time to progressive disease at a current tumour site, even when stratified for a potentially confounding measure of spread of disease, whereas progesterone receptor status positive is important with regard to disease progression at new sites only.

Antineoplastic Agents, Hormonal↗

PubMed1997

Basic Treatment Equivalent (BTE): a new measure of linear accelerator workload.

The measurement of linear accelerator workload in radiation oncology departments is usually based on the number of fields treated per unit time. However, this approach ignores variations in treatment complexity. This prospective study, was designed to measure treatment workload directly, taking into account the variations in complexity of different treatment techniques. From this, a model was to be developed, which would be simple to apply and reproducible, both within and between radiation oncology departments in Australasia. It would provide a realistic basis for assessing treatment costs and enable the comparison of patient throughput between departments. This paper describes the derivation of the model. Over a 4-week period in the Radiation Oncology Department of Westmead Hospital, all fractions of radiotherapy were timed. The data collected included: tumour site; treatment intent; number of fields; number of wedges, compensators and shielding blocks; fraction number; patient age; performance status; and need for general anaesthesia. Multivariate modelling was performed to identify factors that significantly affected fraction duration, so that these could be used to develop a model of resource utilization. The durations of 2371 fractions were measured in 219 patients. Seventy-five per cent of fractions were given with radical intent. The factors found to influence fraction duration on multivariate modelling were: number of fields; number of shielding blocks; first treatment fraction; need for anaesthesia; and performance status. The number of wedges and compensators were also found to be significant but were not included in the model in order to maintain simplicity. This was felt to be necessary if the model is to be applied to the widest possible variety of machines. A model of resources utilization called 'Basic Treatment Equivalent' (BTE) was derived, which incorporated these factors. When tested at Westmead Hospital, this model accurately reflected the predicted BTE value over a further 1-week study period. This model of linear accelerator use, which incorporates complexity has been derived and evaluated in one radiation oncology department. This requires further prospective testing before its widespread use. The model appears to reflect linear accelerator workload better than previous measures. An Australasian study to validate the model further will be undertaken. If adopted, this model has implications for comparative workload reports, diagnostic-related groups, waiting list calculations, and patient scheduling.

Efficiency↗

PubMed1997

An assessment of the Basic Treatment Equivalent (BTE) model as measure of radiotherapy workload.

Current methods of linear accelerator workload analysis in radiation oncology use patients per hour or fields per hour as the basic unit of measurement but fail to take account of the variations in complexity of different treatment techniques. The Basic Treatment Equivalent (BTE) model of productivity assessment has been derived as a potentially better measure of workload because it includes a complexity factor. This model has now been tested prospectively in ten radiation oncology departments in New South Wales and compared with the numbers of fields and patients per hour. Over a 4-week period there were 50,115 fields administrated in 18,466 fractions in 441 hours of machine time in ten radiation oncology departments. The average productivity results for all departments were 4.18 patients, 11.25 fields and 5.66 BTE per hour. When compared with patients per hour and fields per hour, there was less variability of BTE per patient per hour in all departments, suggesting that most departments deliver radiation therapy in a consistent way, which is not appropriately reflected in the numbers of fields or patients per hour. Departments that were able to treat a high number of patients or fields per hour were able to do so because they used less complicated techniques or had a less complicated casemix of patients. The BTE model allows for variations in the complexity of treatment techniques, is simple to apply, and is reproducible under different conditions in different departments. Following revision of the model, an Australasian study is now proposed. The confirmation of our findings will have significant implications for resource utilization comparisons, patient time allocations, waiting list estimates and cost-benefit analysis.

Efficiency↗

PubMed1997

Medroxyprogesterone acetate addition or substitution for tamoxifen in advanced tamoxifen-resistant breast cancer: a phase III randomized trial. Australian-New Zealand Breast Cancer Trials Group.

PURPOSE: To determine whether a strategy of adding medroxyprogesterone acetate (MPA) to tamoxifen (TAM) is superior to the substitution of MPA for TAM among women with advanced breast cancer and disease progressing on TAM. To assess the patterns or response and subsequent progression in sites and tissues according to prior involvement and treatment. PATIENTS AND METHODS: Two-hundred-fifteen postmenopausal women with advanced breast cancer progressing on TAM after receiving TAM for at least six months were randomized: 109 to add MPA 500 mg/day orally (TAM + MPA), and 106 to stop TAM and to substitute MPA. RESULTS: There were no significant differences between the groups with respect to complete plus partial response rates: TAM + MPA 10%, MPA 9%, median time to progression TAM + MPA 3.0 months, MPA 4.5 months, or median overall survival, TAM + MPA 17.2 months, MPA 18.4 months. In a multivariate model, prognostic factors significant for a shorter time to disease progression were worse for performance status, involvement of more than one tissue, prior radiotherapy, and shorter time from recurrence after primary therapy to randomization. Adjusting for these factors, treatment with TAM + MPA was associated with a higher relative risk for disease progression, with a hazards ratio of 1.31, but this was not significant (95% confidence interval, 0.98 to 1.74; P = .067). However, in an exploratory analysis, the time to disease progression, among patients with progesterone receptor positive (PR+) tumors, was 6.3 months with MPA versus 2.9 months with TAM + MPA, with a hazards ratio of 1.92 (95% confidence interval, 1.12 to 3.32; P = .02). There was a significant interaction, P = .04, between PR status and treatment, indicating an advantage to treatment substitution for those who have PR+ tumors. Tumor response occurred in 14% of assessed metastatic sites. Subsequent progression occurred in a new tissue alone in 13% of patients, in both new and previously involved (old) tissues in 76%, and in old tissues only in 11%. In 23% of patients, progression occurred only at a new site, in 50% at both old and new sites, and in 27% only at old sites. No significant differences in the patterns of response or progression were seen in the different treatment groups. CONCLUSION: Among women with breast cancer whose disease is progressing after at least six months of treatment with TAM, there is no advantage to maintaining TAM when MPA is to be given. An overall effect of treatment on the pattern of failure at old sites or at new sites or tissues cannot be discerned.

Aged↗

PubMed1995

Applying Cox regression to competing risks.

Two methods are given for the joint estimation of parameters in models for competing risks in survival analysis. In both cases Cox's proportional hazards regression model is fitted using a data duplication method. In principle either method can be used for any number of different failure types, assuming independent risks. Advantages of the augmented data approach are that it limits over-parametrisation and it runs immediately on existing software. The methods are used to reanalyse data from two well-known published studies, providing new insights.

Analysis of Variance↗