Lung cancer has the highest global incidence among cancers excluding nonmelanoma skin cancer and the highest mortality (1). Radiotherapy (RT) is an effective, evidence-based, and guideline-recommended treatment for patients with lung cancer, both for improving outcomes and for palliating symptoms such as shortness of breath, bleeding and pain (2-6). However, RT is underdeveloped and underutilized worldwide, especially in low-and middle-income countries (LMIC) (7). This has been estimated to cause significant excess morbidity and mortality across a range of cancers, including lung cancer (8).
Expansion of RT resources is complex and costly, but can be cost-effective when planned appropriately (7). Optimal radiotherapy utilization rate (ORUR) and actual radiotherapy utilization rate (ARUR) are common metrics used to forecast such planning. ORUR is the percentage of patients for whom RT is indicated as a treatment option at least once during a time period, and ARUR is the percentage of patients who actually received RT during a time period. The gap between ORUR and ARUR, combined with data on fractionation, retreatment, and incidence for each cancer type, can be used to estimate the unmet demand for RT. In this study, we perform a systematic review of reported ORUR and ARUR for lung cancer.
A systematic review of the literature was performed per the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines (9). PubMed was searched in January 2019 for articles in English from January 2009 to January 2019. A search strategy was performed using keywords including “utilization”, or “underutilization”, or “demand”, or “epidemiologic”, or “benchmark”, and “radiotherapy”, or “radiation therapy”, or “irradiation” or “cancer”. Title and abstracts were screened for full-text review independently by W Liu and A Liu, with discrepancies settled by consensus. The bibliographies of identified articles were also searched for potential additional studies. Eligible studies provided ARUR or ORUR for lung cancer, small cell lung cancer (SCLC), or non-small cell lung cancer (NSCLC). Included ARUR were based on at least 1,000 patients who were diagnosed or treated in 2009 or later. Included ORUR were based on evidence review or ARUR in 2009 or later. Full-text review was performed on remaining articles and articles were excluded where appropriate. Data abstracted from the final articles for inclusion included: study details (source of patient data, sample size), patient details (diagnosis, stage, time of diagnosis), treatment details (time of RT, intent of RT, ARUR, and ORUR) and finally methodological details (method used for estimating ORUR). Data abstraction included estimated values from figures where corresponding numerical values were not presented.
The initial search strategy yielded 1,627 unique abstracts. After title and abstract review, 105 articles were determined to be appropriate for a full-text review. From these, a final set of 21 articles met all inclusion criteria and were suitable for data abstraction (Figure 1).
Of the eight papers that estimated ORUR for lung cancer (Table 1) (7,10-16), six used an evidence-based methodology (7,10-14), one used the Malthus model (15) and one used criterion-based benchmarking (CBB) (16). Two of the six papers that conducted evidence-based estimates of ORUR were performed by the Australian Collaboration for Cancer Outcomes Research and Evaluation (CCORE) group and included systematic reviews of indications for RT (10,11). The remaining four papers were based on the CCORE model and applied different epidemiological data (7,12-14).
Lifetime ORUR for lung cancer were 61% in England using the Malthus model, 62% in Ontario, Canada using CBB, and 77% to 82% using the CCORE evidence-based model. Evidence-based estimates of lifetime ORUR for NSCLC and SCLC were 80% and 59%, respectively (11).
Fifteen papers presented ARUR on lung cancer, SCLC, or NSCLC, including overall ARUR (Table 2), palliative intent ARUR (Table 3), and curative intent ARUR (Table 4) (14,16-29). Measured lifetime ARUR was not available, but lifetime ARUR was estimated using the multicohort utilization table (MCUT) method in Ontario, Canada to be 52% (11). Observation period and method used to calculate ARUR were inconsistent.
Overall ARUR for lung cancer was presented in 6 papers and ranged from 22% in Central Poland to 52% in Ontario, Canada. Overall ARUR for Stage IA NSCLC in the United States of America (USA) increased from 21% in 2009 to 29% in 2012. Overall ARUR for stage I SCLC in the USA ranged from 44% to 53% between 2009 and 2013. Four papers presented palliative intent ARUR ranging from 12% in Central Poland to 47% in Norway. Six papers presented curative intent ARUR on lung cancer, SCLC, or NSCLC. Curative intent RT was variably defined. Curative intent ARUR for stage I SCLC in the USA was 36% to 38%. Stereotactic body radiotherapy (SBRT) use for stage I SCLC in the USA increased from 3% to 6% and conventional external beam radiotherapy (EBRT) decreased between 2009 and 2013 in the USA. For stage I NSCLC, curative intent ARUR was 12% in Europe and England, and 7% to 13% of patients in the USA underwent SBRT.
Lung cancer is the second most common indication for RT globally (7) and has consistently been demonstrated to be the most common indication for palliative RT (18,24,25). In this systematic review, we summarized ARUR and ORUR metrics for lung cancer, and found that lung RT remains underutilized. As lung RT has been demonstrated to be cost-effective (7,30), we would advocate that strategies to optimize its utilization should be prioritized.
Lifetime ORUR for lung RT ranged from 61% to 82%. Evidence-based estimates, the Malthus Model, and CBB are three methods used to estimate lung ORUR, and each has associated strengths and weaknesses. Evidence-based estimates are based on a systematic review to determine indications for RT and estimates of the incidence of each indication in a population. Advantages include transparent methodology and the flexibility to adapt the model to different populations and with changes to indications (31). One weakness of the model is reliance on epidemiological data, which may vary in quality. Population-based registries frequently do not include information such as surgical margins, comorbidities and performance status, and this data may be excluded or estimated from less representative sources (31).
The Malthus model uses the evidence-based estimate method and Monte-Carlo simulation. In the one study using Malthus, results were based on local and regional epidemiological data in England. Advantages and disadvantages are mostly consistent with evidence-based estimates. In contrast to the CCORE (Australian) evidence-based estimates, the Malthus model incorporates surgical rates and patient factors such as age, co-morbidities, and preferences (15).
CBB assumes the ORUR to be the ARUR of benchmark populations with optimal access to RT and appropriate decision making. The primary advantage of CBB is that it is based on real-world data. Clinical decisions regarding RT utilization may appropriately deviate from guidelines based on patient factors such as co-morbidities and preferences, and this cannot always be accounted for using other methods to estimate ORUR (32). In the study using CBB with Ontario, Canada data, the benchmark population was identified to be patients diagnosed at cancer centres with an associated RT facility (16). The one-year and lifetime ORUR based on the benchmark population were 54% and 62%, compared to 45% and an estimated 52% in the overall Ontario population. A weakness of this model is that no benchmark population can indeed provide optimal access to RT and decision-making. Additionally, unrecognized barriers to RT may result in underestimation of ORUR, while incentives to provide RT may result in overestimation. Another weakness of CBB is that the estimate cannot be easily modified for changes in indications for RT or epidemiological data.
Additional factors need to be considered from the data presented herein. The Malthus model and CBB produced lower ORUR estimates of 61–62% compared to the CCORE evidence-based estimates of 77–82%, and these were closer to the reported ARURs. One hypothesis for this observed difference may be that patient age, co-morbidities and preferences are reflected in the Malthus model and CBB, but not in the CCORE evidence-based estimates. Lung cancer patients frequently are older, with more co-morbidities and lower performance status. As such, even if RT may be ‘indicated’, patients may elect not to undergo RT, or referring physicians may deem a patient not eligible for RT (14,32).
ARUR data is limited by the unspecified or short observation period after diagnosis, and inconsistent methods used to calculate ARUR (33). However, despite the lack of measured lifetime ARUR, there is clear underutilization of RT for lung cancer. Lifetime ARUR in Ontario, Canada, was estimated using the MCUT method to be 52% (16) and Lievens et al. reported 4- to 5-year ARUR of 46% (14), compared to lifetime ORUR of 61% to 82%. One-year ORUR based on CBB was 54% (16), compared to reported one-year ARUR of 44% to 46%. The available 1-year ARUR do not approximate lifetime ARUR, as close to half of patients who die of lung cancer require RT in their last year or two years of life (24,25). Long-term ARUR may be especially important in the era of increasingly effective systemic therapies. As immunotherapy following chemoradiation is now considered the standard of care for unresectable locally advanced NSCLC (34), and as immunotherapy and targeted therapies have resulted in survival improvements in metastatic lung cancer, further research focusing on lifetime ARUR in advanced lung cancer is warranted.
In addition to research of ARUR in advanced lung cancers, other gaps include the limited information for ARUR in LMICs, where the majority of patients with lung cancer live (35), and in indigenous populations. The majority of existing ARUR and ORUR literature is from North America, Australia or Europe. RT development is crucial in LMICs due to the increased lung cancer mortality (36) and the very limited access to surgery (37) and systemic therapy compared to high-income countries (HIC). While we cannot exclude the possibility that data for LMICs may be available in publications in other languages, another barrier for this type of research is the underdevelopment of population-based cancer registries in some areas. As an example, in Africa, Asia, and Central and South America, 2%, 6% and 8% of the regional populations were included in robust cancer registries, compared to 95% in North America (38). Even within HICs, ARUR data are not available for indigenous populations, who compared to non-indigenous patients from the same country, have increased risk of cancer mortality (39). Further development of cancer registries and calculation of ORUR and ARUR where data are available will allow for more accurate estimation of unmet RT needs.
Based on this systematic review, lifetime ORUR for lung cancer patients ranged from 61% to 82%. ORUR of 61–62% based on CBB and the Malthus model are closer to ARUR compared to evidence-based estimates. Available ARUR data suggest an underutilization of RT in all populations. Almost all data were from North America, Australia, or Europe. No ORUR or ARUR for LMICs were reported.
Conflicts of Interest: Dr. Louie has received honoraria from Varian Medical Systems Inc. and AstraZeneca. The other authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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