Clinical Prioritisation for Curative Radiotherapy: A Local Waiting List Initiative

Ethical dilemmas in prioritizing patients for scarce radiotherapy resources

BACKGROUND

Radiotherapy is an essential component of cancer treatment, yet many countries do not have adequate capacity to serve all patients who would benefit from it. Allocation systems are needed to guide patient prioritization for radiotherapy in resource-limited contexts. These systems should be informed by allocation principles deemed relevant to stakeholders. This study explores the ethical dilemmas and views of decision-makers engaged in real-world prioritization of scarce radiotherapy resources at a cancer center in Rwanda in order to identify relevant principles.

METHODS

Semi-structured interviews were conducted with a purposive sample of 22 oncology clinicians, program leaders, and clinical advisors. Interviews explored the factors considered by decision-makers when prioritizing patients for radiotherapy. The framework method of thematic analysis was used to characterize these factors. Bioethical analysis was then applied to determine their underlying normative principles.

RESULTS

Participants considered both clinical and non-clinical factors relevant to patient prioritization for radiotherapy. They widely agreed that disease curability should be the primary overarching driver of prioritization, with the goal of saving the most lives. However, they described tension between curability and competing factors including age, palliative benefit, and waiting time. They were divided about the role that non-clinical factors such as social value should play, and agreed that poverty should not be a barrier.

CONCLUSIONS

Multiple competing principles create tension with the agreed upon overarching goal of maximizing lives saved, including another utilitarian approach of maximizing life-years saved as well as non-utilitarian principles, such as egalitarianism, prioritarianism, and deontology. Clinical guidelines for patient prioritization for radiotherapy can combine multiple principles into a single allocation system to a significant extent. However, conflicting views about the role that social factors should play, and the dynamic nature of resource availability, highlight the need for ongoing work to evaluate and refine priority setting systems based on stakeholder views.

Radiotherapy scheduling using prime numbers

Background

The optimal delivery of radiation therapy to achieve maximum tumour cell kill while limiting damage to normal tissues underlies any radiation therapy treatment protocol. The biological effectiveness of radiation therapy is closely related to cellular reproductive activity. The scheduling of dose fraction to a time where actively dividing cells are at their most radiosensitive stage (RS) has potential to enhance therapeutic efficacy.

Materials and methods

A prime number is a natural number >1 whose only divisors are 1 and the number itself.

Purpose

We propose that the use of prime numbers in the scheduling of radiotherapy treatments could maximise biological effectiveness by facilitating the irradiation of the greatest number of cells at their most RS stage, and ultimately improve the therapeutic ratio of radiation therapy.

Conclusions

The theoretical clinical implementation of this concept into the scheduling of radiation therapy is discussed.

Utilitarian prioritization of radiation oncology patients based on maximization of population tumour control

An objective method for establishing patient prioritization in the context of a radiotherapy waiting list is investigated. This is based on a utilitarian objective, being the greatest probability of local tumour control in the population of patients. A numerical simulation is developed and a clinical patient case-mix is used to determine the influence of the characteristics of the patient population on resulting optimal patient scheduling. With the utilitarian objective, large gains in tumour control probability (TCP) can be achieved for individuals or cohorts by prioritizing patients for that fraction of the patient population with relatively small sacrifices in TCP for a smaller fraction of the population. For a waiting list in steady state with five patients per day commencing treatment and leaving the list (and so with five patients per day entering the list), and a mean wait time of 35 days and a maximum of 90 days, optimized wait times ranged from a mean of one day for patients with tumour types with short effective doubling times to a mean of 66.9 days for prostate cancer patients. It is found that, when seeking the optimal daily order of patients on the waiting list in a constrained simulation, the relative rather than absolute value of TCP is the determinant of the resulting optimal waiting times. An increase in the mean waiting time mostly influences (increases) the optimal waiting times of patients with fast-growing tumours. The proportional representation of groups (separated by tumour type) in the patient population has an influence on the resulting distribution of optimal waiting times for patients in those groups, though has only a minor influence on the optimal mean waiting time for each group.

Waiting times for diagnosis and treatment of head and neck cancer in Denmark in 2010 compared to 1992 and 2002

BACKGROUND AND AIM

Significant tumour progression was observed during waiting time for treatment of head and neck cancer. To reduce waiting times, a Danish national policy of fast track accelerated clinical pathways was introduced in 2007. This study describes changes in waiting time and the potential influence of fast track by comparing waiting times in 2010 to 2002 and 1992.

METHODS

Charts of all new patients diagnosed with squamous cell carcinoma of the oral cavity, pharynx and larynx at the five Danish head and neck oncology centres from January to April 2010 (n=253) were reviewed and compared to similar data from 2002 (n=211) and 1992 (n=168).

RESULTS

The median time to diagnosis was 13 days (2010) versus 17 days (2002; p<0.001) and 20 days (1992; p<0.001). Median days from diagnosis to treatment start were 25 (2010) versus 47 (2002; p<0.001) and 31 (1992; p<0.001). Total pre-treatment time was median 41 days in 2010 versus 69 days (2002) (p<0.001) and 50 days (1992; p<0.001). Significantly more diagnostic imaging was done in 2010 compared to 2002 and 1992. When compared to current fast track standards the adherence to diagnosis improved slightly from 47% (1992) to 51% (2002) and 64% (2010); waiting time for radiotherapy was within standards for 7%, 1% and 22% of cases, respectively; waiting time for surgery was within standards for 17%, 22% and 48%, respectively.

CONCLUSION

The study showed a significant reduction in delay of diagnosis and treatment of head and neck cancer in 2010, but still less than half of all patients start treatment within the current standards.

From a Waiting List to a Priority List: A Computerized Model for an Easy-to-Manage and Automatically Updated Priority List in the Booking of Patients Waiting for Radiotherapy

Aims and background

Waiting time for radiotherapy is a major problem in clinical practice. We developed a model to create a priority list of patients waiting for radiotherapy according to clinical criteria, where booking of patients is not on a “first-come, first-served” basis and where prioritization has not been left up to individual discretion.

Methods

The system is based on an algorithm that assigns to each patient a personal code (priority code, PC) that can be used as a continuous variable to have a priority list. PCpatient = D0patient + PWTsubgroup of treatment. Palliative treatments were categorized according to the clinical urgency. Radical treatments were stratified by primary tumors, by the setting of treatment (preoperative, curative, postoperative) and by the main prognostic factors. Each subgroup of patients has a “priority waiting time” (PWT subgroup of treatment). Calculation of the PC starts from a differentiated date according to clinical scenario [Reference date (D0)], which is taken from the clinical history of the patient.

Results

Patients are differentiated according to clinical criteria and according to time elapsed from diagnosis. The priority list can be automatically updated day by day. Delays in patient referral or imaging availability are minimized.

Conclusions

The model represents a tool for an objective and automatic prioritization of the patients who are waiting for radiotherapy.

Do triage systems in healthcare improve patient flow? A systematic review of the literature

OBJECTIVES

Triage processes are often used by Emergency Departments to sort patients according to urgency or type of service required. Triage may also be used in a broad spectrum of other health services and not just emergency departments. Triage systems may be used to ensure the most urgent patients get timely service, but do they have an effect on patient flow?

METHODS

We conducted a systematic review by searching five electronic databases (until August 2009) combining the elements 'triage' and 'patient flow', complemented by hand searching reference lists and citation tracking. We identified and assessed the quality of 25 articles that met inclusion criteria. Population, setting, design and results were extracted and a process of descriptive synthesis applied. Effect sizes for waiting time were compared for seven studies in which sufficient data could be extracted.

RESULTS AND CONCLUSION

Moderate evidence exists from a range of health services that the ability to combine triage and initial treatment in less resource intensive cases can have a positive effect on patient flow. There is conflicting evidence that triage systems that only prioritize patients, without providing any treatment, improve overall patient flow, although tailoring triage criteria more specifically to the patient population or using triage to prioritize treatable cases may be of benefit.

A model for managing patient booking in a radiotherapy department with differentiated waiting times

BACKGROUND

In Denmark, the waiting time from the ready-to-treat date to the first radiotherapy fraction is by national legislation guaranteed not to exceed 4 weeks. This guarantee has now been tightened for some specific diagnoses as it is required that e.g. intestinal and head and neck cancer patients have to be treated without unnecessary delays. Thus, patients with these tumour sites have to start radiotherapy treatment immediately after diagnosis, if it is their primary treatment modality. Previously, patients have been booked at the first empty time slot after their ready-to-treat date. Now, booking has to take the differentiated waiting times into account. To facilitate this, a model has been developed. It is used to manage the booking of patients, reserve accelerator capacity for patients with no waiting time and establish the waiting times for other patients.

METHODS

The patients are divided into categories according to their waiting time guarantee and for each category a maximum waiting time is defined. The required daily accelerator capacity and average new starts rate for each waiting time category has been determined from the actual patient case-mix in the department. To account for variations in treatment capacity, a prospective daily accelerator capacity is set. Based on the prospective capacity, preparation times, maximum waiting times, and new starts rates, a maximum booking curve (MBC) and a lower limit curve (LLC) are derived. They show the daily maximum and minimum limits, respectively, for booking at future dates.

RESULTS

The method is evaluated by a retrospective analysis of actual number of appointments booked compared to the MBC and LLC in situations of both excessive workload and ineffective use of capacity.

CONCLUSION

The model represents a tool for effectively managing the capacity in a radiotherapy department with differentiated waiting times. It improves the transparency of the booking process and prospective waiting times can easily be derived on a daily basis.

Clinical outcome for chemoradiotherapy in carcinoma of the cervix

AIMS

Two recent meta-analyses have shown a survival advantage for the addition of concurrent chemotherapy to radiotherapy in the treatment of cervical cancer. However, there is insufficient information available on late toxicity and few data from UK practice. The aims of this study were to examine treatment outcomes (survival and toxicity) in patients with cervical cancer treated with chemoradiation and to compare these with outcomes in patients treated with radiation alone.

MATERIALS AND METHODS

Between July 2000 and December 2003, 75 patients with cervical cancer were treated with chemoradiation. Case notes were reviewed retrospectively. Acute and late toxicity were recorded, with late toxicity graded using the Franco-Italian glossary. The median age was 47 years. All patients were staged with examination under anaesthesia and magnetic resonance imaging scans. Forty-two patients were treated with concurrent chemoradiation alone and 33 patients were treated with a combination of neoadjuvant and concurrent chemoradiation. This was due to waiting list problems. The chemotherapy used was cisplatin 40 mg/m(2) weekly with radiotherapy, (the neoadjuvant dose was 60 mg/m(2) 3 weekly). External beam radiotherapy was given to the pelvis (40-45 Gy/20 fractions/4 weeks) followed by low dose rate brachytherapy (22.5-32.5 Gy to point A). Patients who were unable to have brachytherapy were given an external beam boost (15-20 Gy/8-10 fractions).

RESULTS

The 3-year overall survival rate was 70%, with an estimated 5-year overall survival rate of 60%. The 3-year disease-free survival was 63.6%, with an estimated 5-year disease-free survival rate of 55%. Compared with the cohort of 183 patients from the Christie Hospital in a 1993 audit, there was a trend towards improved overall survival from 49 to 60% (P=0.06), which may become significant with longer follow-up. There were seven patients (9.3%) with grade 3 toxicity and no cases of grade 4 toxicity. In comparison with patients treated in the 1993 audit, the late toxicity rate has increased from 3.4 to 9.3%, but this was not statistically significant (P=0.14).

CONCLUSION

There was a trend towards improved survival with concurrent chemoradiation in this cohort of patients that may become significant with longer follow-up.

Managing workflow in treatment planning using standard spreadsheet software

Aims: Recent years have seen an expansion of UK radiotherapy treatment capacity with a drive to reduce radiotherapy waiting times. Consequently, the time available for planning patients is decreasing. In this context, management of treatment planning workflow in the Princess Royal Hospital is described and monthly planning times are presented from September 2003 onwards.

Materials and Methods: After patients are imaged, patient name, unit number and appointments are available to the planning spreadsheet via a link to the radiotherapy information system. The planning spreadsheet is in descending order of appointment date. Treatment planning staff select the first available task, taking account of individual competencies. At plan completion, the patient record is moved to the completed list.

Results: Since September 2003, patient numbers through treatment planning steadily increased from around 90 a month to about 130 currently. Planning times decreased from 11 to 7 workdays.

Conclusions: Workflow through treatment planning is indirectly managed and the approach allows for day-to-day staffing fluctuations and competency levels. There is instant information on planning status for all patients throughout the department, building up a record as part of the work process. Bottlenecks and staff training needs can be analysed by reviewing the historic patient workload.

Improved survival after concurrent weekly cisplatin and radiotherapy for cervical carcinoma with assessment of acute and late side-effects

AIMS

A recent meta-analysis has shown a survival advantage for the addition of concurrent chemotherapy to radiotherapy in the treatment of cervical carcinoma. Controversy persists about the most appropriate chemotherapy schedule and whether similar results for tumour control and toxicity may be achieved with optimally delivered radiotherapy. A single-centre experience of a concurrent chemotherapy regimen is presented.

MATERIALS AND METHODS

All women treated with concurrent chemoradiotherapy at a university hospital from 1 January 1999 to 1 May 2002 were identified. Acute and late complications were scored using the National Cancer Institute Common Toxicity Criteria and RTOG/ EORTC system, respectively. Univariate and multivariate analyses were carried out to examine the relationship between demographics, stage, overall treatment time, radiotherapy dose, selectron insertion, number of chemotherapy cycles and occurrence of acute and late toxicity.

RESULTS

Seventy-nine women received concurrent weekly cisplatin (40 mg/m2) with radiotherapy. Thirty-eight per cent had early tumours (FIGO IIA or less) and 62% had locally advanced tumours. Twenty-eight per cent of women had surgery as part of primary treatment. Radiation technique included external-beam pelvic radiotherapy (EBRT) (45-50.4 Gy in 25-28 fractions) and medium-dose rate brachytherapy single insertion (25-27 Gy to point A) or EBRT alone. Median overall treatment time was 49 days (range 23-91 days). Three-year survival rate was 87% (95% confidence interval [CI] 79-95%). Three-year, progression-free survival rate was 75% (95% CI 65-85%). At a median follow-up of 35 months: 27 (34%) women experienced 45 episodes of acute grade 3 or 4, and eight women (10%) experienced 12 late grade 3 or 4 complications.

CONCLUSIONS

Weekly cisplatin 40 mg/m2 concurrent with radiotherapy is well tolerated when given to an unselected population of patients. Survival rates seem to be excellent, with both local control and overall survival being at least as good as those in published randomised trials.

Managing waiting time for radiotherapy: A single machine unit experience

Waiting time (WT) for radiotherapy (RT) is a significant clinical problem. This paper examines various strategies for managing WT for patients treated with radical and palliative intent in the new setting of a rural single machine unit in Australia. Cohorts of patients undergoing both radical and palliative RT in Bendigo had their WT prospectively recorded. Matched cohorts from the hub centre (Peter MacCallum Cancer Centre, Melbourne) treated with palliative intent were also collated. Strategies implemented included a devoted priority meeting, palliative points system, and reallocation of appointment times. The audit was to continue until best practice guidelines were bettered. Three cohorts of patients were compared. There is a significant trend for increasing numbers of patients treated per month since the centre opened (P < 0.0001). The ratio of palliative to radical intent patients remained stable between 46 and 52%. Mean WT for palliative RT reduced from 25 days in the first cohort to 7 days in the final cohort (P < 0.0005). Waiting time for palliative RT was initially longer at Bendigo than the hub centre (P < 0.0005), but by the final cohort there was a non-significant difference favouring the Bendigo cohort (P = 0.26). Waiting time for radical treatment also improved throughout the three cohorts in Bendigo (P < 0.0005). A number of new strategies have successfully resulted in the abolition of lengthy WT for RT in Bendigo despite the increasing demand for the RT service.