Diagnostic delay and survival in high-grade gliomas - evidence of the 'waiting time paradox'?

Patient- and parent-reported diagnostic delay in children with central nervous system tumors in Denmark

BACKGROUND

Diagnostic delays in childhood tumors of the central nervous system (CNS) pose a significant challenge. The aim of this study was to map diagnostic delay and presenting symptoms in Denmark.

METHODS

The study was a retrospective questionnaire study, mapping delay and symptoms in pediatric patients (0-17 years), diagnosed with a CNS tumor from 2015 to 2019. Descriptive analysis was performed to measure delay in days, reported as total diagnostic interval (TDI), patient interval (PI), and diagnostic interval (DI). Analysis of symptoms, contacts to healthcare professionals, and socioeconomic status was also performed.

RESULTS

We included 89 patients (median age 7.0 years, 54% male). The TDI was median of 106 days (range: 0-2694 days). Low-grade tumors had longer TDI than high-grade tumors (125 vs. 43 days; p ≤ .02). Patients aged 15-17 displayed the longest TDI (median 665 days). Number of symptoms at onset were inversely associated with longer TDI in patients presenting one symptom (247 days) and patients presenting two to three (110 days) or greater than three complaints (66 days). PI was not associated with sex (p = .14), tumor grade (p = .63), location (p = .32), or socioeconomic status (p = .82). Most frequent single complaint at onset was headache (19%), most frequent combination of symptoms was headache and vomiting (60%).

CONCLUSION

We found TDIs longer than reported in contemporary publications. TDI was longer in patients with low-grade tumors and only few symptoms at the time of onset. The findings support the crucial need of awareness and improved diagnostic tools to recognize and interpret symptoms to promote timely diagnosis.

Delay in the diagnosis of paediatric brain tumours: a systematic review

PURPOSE

A delay in obtaining a diagnosis has been associated with inferior outcomes across several cancer types, including paediatric brain tumours. However, no clear evidence exists in this population. We aimed to quantify the reported pre-diagnostic symptom interval (PSI) as the time from onset of first symptoms to diagnosis in the literature, in addition to evaluating the relationship between delay and outcomes, including survival.

METHODS

A systematic review of the literature was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, Wiley Online Library, Web of Science and EMBASE databases were searched. We considered all sources published between 1st January 2010 and 5th November 2022. Children and adolescents aged under 21 years, with new symptomatic primary brain tumour diagnoses, were included.

RESULTS

Of 3123 studies identified, 11 were included for analysis. Owing to study heterogeneity, a quantitative meta-analysis was not feasible; however, a narrative synthesis was performed. The median reported PSI varied widely, ranging between 28 and 760.8 days. We failed to identify a significant association between prolonged PSI and inferior overall survival. Few factors were consistently associated with prolonged PSI, amongst them only tumour grade and patient age.

CONCLUSION

Delayed diagnosis of paediatric brain tumours was not associated with inferior survival within this review. This 'waiting time' paradox appears to result from several confounding factors including tumour biology, patient population and key systematic factors that were inconsistently reported. Diagnostic interval clearly presents a complex variable, reflected further by disparity in the reporting of delay within the literature. Ultimately diagnostic interval is unlikely to provide a meaningful representation for all tumour types and should not detract from sharp clinical acumen and prompt diagnosis.

Impact of the SARS-CoV-2 pandemic on the survival of patients with high-grade glioma and best practice recommendations

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has changed the clinical day-to-day practice. The aim of this study was to evaluate the impact of the pandemic on patients with high-grade glioma (HGG) as well as to derive best practice recommendations. We compared a multi-institutional cohort with HGG (n = 251) from 03/2020 to 05/2020 (n = 119) to a historical cohort from 03/2019 to 05/2019 (n = 132). The endpoints were outcome (progression-free survival (PFS) and overall survival (OS)) as well as patterns of care and time intervals between treatment steps. The median OS for WHO grade 4 gliomas was 12 months in 2019 (95% Confidence Interval 9.7-14.3 months), and not reached in 2020 (p = .026). There were no other significant differences in the Kaplan-Meier estimates for OS and PFS between cohorts of 2019 and 2020, neither did stratification by WHO grade reveal any significant differences for OS, PFS or for patterns of care. The time interval between cranial magnetic resonance imaging (cMRI) and biopsy was significantly longer in 2020 cohort (11 versus 21 days, p = .031). Median follow-up was 10 months (range 0-30 months). Despite necessary disease containment policies, it is crucial to ensure that patients with HGG are treated in line with the recent guidelines and standard of care (SOC) algorithms. Therefore, we strongly suggest pursuing no changes to SOC treatment, a timely diagnosis and treatment with short time intervals between first symptoms, initial diagnosis, and treatment, as well as a guideline-based cMRI follow-up.

Between-hospital variation in time to glioblastoma surgery: a report from the Quality Registry Neuro Surgery in the Netherlands

OBJECTIVE

Patients with glioblastoma are often scheduled for urgent elective surgery. Currently, the impact of the waiting period until glioblastoma surgery is undetermined. In this national quality registry study, the authors determined the wait times until surgery for patients with glioblastoma, the risk factors associated with wait times, and the risk-standardized variation in time to surgery between Dutch hospitals. The associations between time to surgery and patient outcomes were also explored.

METHODS

Data from all 4589 patients who underwent first-time glioblastoma surgery between 2014 and 2019 in the Netherlands were collected by 13 hospitals in the Quality Registry Neuro Surgery. Time to surgery comprised 1) the time from first MR scan to surgery (MTS), and 2) the time from first neurosurgical consultation to surgery (CTS). Long MTS was defined as more than 21 days and long CTS as more than 14 days. Potential risk factors were analyzed in multivariable logistic regression models. The standardized rate of long time to surgery was analyzed using funnel plots. Patient outcomes including Karnofsky Performance Scale (KPS) score change, complications, and survival were analyzed by multivariable logistic regression and proportional hazards models.

RESULTS

The median overall MTS and CTS were 18 and 9 days, respectively. Overall, 2576 patients (56%) had an MTS within 3 weeks and 3069 (67%) had a CTS within 2 weeks. Long MTS was significantly associated with older age, higher preoperative KPS score, higher American Society of Anesthesiologists comorbidity class, season, lower hospital case volume, university affiliation, and resection. Long CTS was significantly associated with higher baseline KPS score, university affiliation, resection, more recent year of treatment, and season. In funnel plots, considerable practice variation was observed between hospitals in patients with long times to surgery. Fewer patients with KPS score improvement were observed after a long time until resection. Long CTS was associated with longer survival. Complications and KPS score decline were not associated with time to surgery.

CONCLUSIONS

Considerable between-hospital variation among Dutch hospitals was observed in the time to glioblastoma surgery. A long time to resection impeded KPS score improvement, and therefore, patients who may improve should be identified for more urgent resection. Longer survival was observed in patients selected for longer time until surgery after neurosurgical consultation (CTS).

A multidisciplinary neuro-oncological triage panel reduces the time to referral and treatment for patients with a brain tumor

Background

Regional collaboration and appropriate referral management are crucial in neuro-oncological care. Lack of electronic access to medical records across health care organizations impedes interhospital consultation and may lead to incomplete and delayed referrals. To improve referral management, we have established a multidisciplinary neuro-oncological triage panel (NOTP) with digital image exchange and determined the effects on lead times, costs, and time investment.

Methods

A prospective cohort study was conducted from February 2019 to March 2020. All newly diagnosed patients referred to Brain Tumor Center Amsterdam were analyzed according to referral pathway: (1) standard referral (SR), (2) NOTP. The primary outcome was lead time, defined as time-to-referral, time-to-treatment, and total time (median days [interquartile range]). Secondary outcomes were costs and time investment.

Results

In total, 225 patients were included, of whom 153 had SR and 72 NOTP referral. Patients discussed in the NOTP were referred more frequently for first neurosurgical consultation (44.7% vs 28.8%) or combined neurological and neurosurgical consultation (12.8% vs 2.5%, P = .002). Time-to-referral was reduced for NOTP referral compared to SR (1 [0.25-4] vs 6 [1.5-10] days, P < .001). Total time decreased from 27 [14-48] days for the standard group to 15 [12-38.25] days for the NOTP group (P = .040). Costs and time investment were comparable for both groups.

Conclusion

Implementation of digital referral to a multidisciplinary NOTP is feasible and leads to more swift patient-tailored referrals at comparable costs and time investment as SR. This quality improvement initiative has the potential to improve collaboration and coordination of multidisciplinary care in the field of neuro-oncology.

Early economic evaluation to guide the development of a spectroscopic liquid biopsy for the detection of brain cancer

OBJECTIVES

An early economic evaluation to inform the translation into clinical practice of a spectroscopic liquid biopsy for the detection of brain cancer. Two specific aims are (1) to update an existing economic model with results from a prospective study of diagnostic accuracy and (2) to explore the potential of brain tumor-type predictions to affect patient outcomes and healthcare costs.

METHODS

A cost-effectiveness analysis from a UK NHS perspective of the use of spectroscopic liquid biopsy in primary and secondary care settings, as well as a cost-consequence analysis of the addition of tumor-type predictions was conducted. Decision tree models were constructed to represent simplified diagnostic pathways. Test diagnostic accuracy parameters were based on a prospective validation study. Four price points (GBP 50-200, EUR 57-228) for the test were considered.

RESULTS

In both settings, the use of liquid biopsy produced QALY gains. In primary care, at test costs below GBP 100 (EUR 114), testing was cost saving. At GBP 100 (EUR 114) per test, the ICER was GBP 13,279 (EUR 15,145), whereas at GBP 200 (EUR 228), the ICER was GBP 78,300 (EUR 89,301). In secondary care, the ICER ranged from GBP 11,360 (EUR 12,956) to GBP 43,870 (EUR 50,034) across the range of test costs.

CONCLUSIONS

The results demonstrate the potential for the technology to be cost-effective in both primary and secondary care settings. Additional studies of test use in routine primary care practice are needed to resolve the remaining issues of uncertainty-prevalence in this patient population and referral behavior.

Timing of glioblastoma surgery and patient outcomes: a multicenter cohort study

BACKGROUND

The impact of time-to-surgery on clinical outcome for patients with glioblastoma has not been determined. Any delay in treatment is perceived as detrimental, but guidelines do not specify acceptable timings. In this study, we relate the time to glioblastoma surgery with the extent of resection and residual tumor volume, performance change, and survival, and we explore the identification of patients for urgent surgery.

METHODS

Adults with first-time surgery in 2012-2013 treated by 12 neuro-oncological teams were included in this study. We defined time-to-surgery as the number of days between the diagnostic MR scan and surgery. The relation between time-to-surgery and patient and tumor characteristics was explored in time-to-event analysis and proportional hazard models. Outcome according to time-to-surgery was analyzed by volumetric measurements, changes in performance status, and survival analysis with patient and tumor characteristics as modifiers.

RESULTS

Included were 1033 patients of whom 729 had a resection and 304 a biopsy. The overall median time-to-surgery was 13 days. Surgery was within 3 days for 235 (23%) patients, and within a month for 889 (86%). The median volumetric doubling time was 22 days. Lower performance status (hazard ratio [HR] 0.942, 95% confidence interval [CI] 0.893-0.994) and larger tumor volume (HR 1.012, 95% CI 1.010-1.014) were independently associated with a shorter time-to-surgery. Extent of resection, residual tumor volume, postoperative performance change, and overall survival were not associated with time-to-surgery.

CONCLUSIONS

With current decision-making for urgent surgery in selected patients with glioblastoma and surgery typically within 1 month, we found equal extent of resection, residual tumor volume, performance status, and survival after longer times-to-surgery.

Time to diagnosis and clinical characteristics in pediatric brain tumor patients

PURPOSE

We aimed to identify factors that affect the time to diagnosis in pediatric brain tumors and investigate the effect of time to diagnosis on clinical outcome.

METHODS

A retrospective study of children with brain tumors aged less than 18 years diagnosed at the University of Tsukuba Hospital over a period of 7 years was conducted.

RESULTS

Eighty-five consecutive patients, with a mean age of 9.1 years, were included in the study. The median interval from symptom onset to diagnosis was 45 days (range 0-1673); median interval from symptom onset to first presentation was 31.0 days; and median interval from first presentation to diagnosis was 13.5 days. Germinoma had the longest interval from symptom onset to first presentation, and from first presentation to diagnosis. Patients presenting with endocrine disorder had a significantly longer interval from symptom onset to first presentation (p = 0.019); those with visual disturbance (p = 0.016) or endocrine disorder (p = 0.030) had significantly longer intervals from first presentation to diagnosis.

CONCLUSION

Pediatric brain tumor patients with germinoma and presenting symptoms of endocrine disorder or visual disturbance have a longer time to diagnosis. Although improved prognosis is not clearly related to a shorter time to diagnosis, we believe that early diagnosis can lead to improved treatment and better quality of life. A detailed medical history and neuroimaging studies at the earliest time possible are important for early diagnosis.

The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

BACKGROUND

Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types.

METHODS

In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15-84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data.

FINDINGS

We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9-9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266-295) and 344 (329-358) additional deaths. For colorectal cancer, we estimate 1445 (1392-1591) to 1563 (1534-1592) additional deaths, a 15·3-16·6% increase; for lung cancer, 1235 (1220-1254) to 1372 (1343-1401) additional deaths, a 4·8-5·3% increase; and for oesophageal cancer, 330 (324-335) to 342 (336-348) additional deaths, 5·8-6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291-3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204-63 229 years.

INTERPRETATION

Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer.

FUNDING

UK Research and Innovation Economic and Social Research Council.

Association between hospital interval and survival in patients with oral cancer: A waiting time paradox

BACKGROUND

In early diagnosis studies on symptomatic cancer, survival was the most recommended outcome. The magnitude and impact of the patient interval and primary care interval is well-known in oral cancer; however, the hospital interval and its influence on surviving this neoplasia are not well known.

AIMS

To quantify the interval between the first contact with the specialist and the start of treatment for patients with oral cancer and to evaluate whether there was a link between this interval and disease survival.

METHODS

We designed a hospital-based study that included 228 patients diagnosed with oral/oropharyngeal squamous cell carcinoma between 1998 and 2008 at A Coruña University Hospital (Spain) who were followed up until 2016. The data were extracted retrospectively from hospital medical charts. The study interval was defined in the context of the "pathways to treatment" model as the interval from the first specialist visit (start point) to the start of treatment (end point). We calculated the total interval (from first symptom to treatment) to evaluate the relative length of the hospital interval, and we considered the variables age, sex, location, comorbidity and tumour classification stage. Survival time was defined as the interval from the first treatment to death or censoring.

RESULTS

The median hospital interval was 20 days, with an interquartile range of 15-29.1 days. The most relevant prognostic variable was the tumour stage (III-IV: Exp. ß = 2.8, p = 0.001). The hospital interval was part of the multivariate model, and its association with mortality showed a V-shaped association, where patients with short hospital intervals (3-18 days) and those with long hospital intervals (26-55 days) had significantly higher mortality than those with medium hospital intervals (19-25 days).

CONCLUSION

The hospital interval represents a relevant interval for the patient's path towards treatment, has prognostic implications and is subject to a severity bias (waiting time paradox) that should be avoided.

Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer

Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.

Diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography in the evaluation of glioma

INTRODUCTION

Identifying glioma grade through imaging allows clinicians to recommend and accurately direct treatment. We sought to quantify the utility of FDG-PET/CT (18F-fluorodeoxyglucose positron emission tomography/computed tomography), alone and in combination with MRI, in identifying high-grade regions of glioma.

METHODS

This is a retrospective review of patients who had an FDG-PET/CT performed as part of the workup of suspected glioma or in follow-up of known glioma. FDG-PET/CT scans were reviewed and uptake in the identifiable lesion coded as none, diffusely or focally increased. Patients also underwent gadolinium-enhanced MRI, noting regions of contrast enhancement. Sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated for identification of high-grade histology (WHO III or IV, or metastatic disease) obtained post-FDG-PET/CT.

RESULTS

Thirty-three patients had 36 FDG-PET/CT and MRI scans followed by histological confirmation (biopsy or debulking). Increased FDG uptake demonstrated a sensitivity of 59% and specificity of 79%, PPV of 81% and NPV of 55% for identification of high-grade histology. MRI demonstrated a sensitivity of 77% and specificity of 86%, PPV of 89% and NPV of 71% for identification of high-grade histology. Only 64% of MRI and FDG-PET/CT scan series were concordant. When FDG-PET/CT and MRI were concordant, a specificity of 100% and PPV of 100% was achieved, however, sensitivity was 79% and NPV was 75%.

CONCLUSION

The combination of FDG-PET/CT and gadolinium-enhanced MRI demonstrated marked improvement in identifying potential high-grade disease over each modality alone. Increased FDG uptake without gadolinium enhancement rarely occurred and identified high-grade histology in a small number of patients. Due to limited sensitivity and NPV, a negative FDG-PET/CT alone, or in combination with MRI, should not guide a decision for observation where surgery would otherwise be recommended.

Health economic evaluation of a serum-based blood test for brain tumour diagnosis: exploration of two clinical scenarios

OBJECTIVES

To determine the potential costs and health benefits of a serum-based spectroscopic triage tool for brain tumours, which could be developed to reduce diagnostic delays in the current clinical pathway.

DESIGN

A model-based health pre-trial economic assessment. Decision tree models were constructed based on simplified diagnostic pathways. Models were populated with parameters identified from rapid reviews of the literature and clinical expert opinion.

SETTING

Explored as a test in both primary and secondary care (neuroimaging) in the UK health service, as well as application to the USA.

PARTICIPANTS

Calculations based on an initial cohort of 10 000 patients. In primary care, it is estimated that the volume of tests would approach 75 000 per annum. The volume of tests in secondary care is estimated at 53 000 per annum.

MAIN OUTCOME MEASURES

The primary outcome measure was quality-adjusted life-years (QALY), which were employed to derive incremental cost-effectiveness ratios (ICER) in a cost-effectiveness analysis.

RESULTS

Results indicate that using a blood-based spectroscopic test in both scenarios has the potential to be highly cost-effective in a health technology assessment agency decision-making process, as ICERs were well below standard threshold values of £20 000-£30 000 per QALY. This test may be cost-effective in both scenarios with test sensitivities and specificities as low as 80%; however, the price of the test would need to be lower (less than approximately £40).

CONCLUSION

Use of this test as triage tool in primary care has the potential to be both more effective and cost saving for the health service. In secondary care, this test would also be deemed more effective than the current diagnostic pathway.

The impact of route of diagnosis on survival in patients with glioblastoma

INTRODUCTION

The standard of care for glioblastoma is maximal debulking surgery followed by chemo-radiotherapy (CRT). Published data show worse outcomes for patients who present with GBM as an emergency. This study investigates prognostic factors in a cohort of GBM patients treated with postoperative CRT, and compares outcomes in patients who present via emergency pathways with those who present through outpatient clinics.

METHODS

Patients with GBM operated on between 1 April 2010 and 5 October 2015 and then treated with postoperative CRT were included in the study. Data were collected from electronic patient records and radiotherapy planning systems. Survival data were censored on 22 March 2016. Univariate and multivariate analyses of prognostic factors were performed.

RESULTS

104 patients were studied; mean age 51.6 years (range 19 to 70 years). Median overall survival (OS) was 16.5 months, with 68.2% and 37.8% alive at 12 and 24 months respectively. On multivariate analysis, improved OS was associated with ECOG Performance Status of 0 (vs ≥1; p = .012), patient age <60 years (vs ≥60 years; p < .001), and surgical debulking or macroscopic complete resection (vs biopsy; p < .001). Patients who presented through emergency medical pathways had worse survival (p = .005).

CONCLUSION

This study supports published data that initial presentation through emergency pathways is associated with worse outcomes in GBM, even in patients who remain fit enough to receive post-operative CRT.

Ovarian Cancer and Comorbidity: Is Poor Survival Explained by Choice of Primary Treatment or System Delay?

Objectives

Comorbidity influences survival in ovarian cancer, but the causal relations between prognosis and comorbidity are not well characterized. The aim of this study was to investigate the associations between comorbidity, system delay, the choice of primary treatment, and survival in Danish ovarian cancer patients.

Methods

This population-based study was conducted on data from 5317 ovarian cancer patients registered in the Danish Gynecological Cancer Database. Comorbidity was classified according to the Charlson Comorbidity Index and the Ovarian Cancer Comorbidity Index. Pearson χ2 test and multivariate logistic regression analyses were used to investigate the association between comorbidity and primary outcome measures: primary treatment (“primary debulking surgery” vs “no primary surgery”) and system delay (more vs less than required by the National Cancer Patient Pathways [NCPPs]). Cox regression analyses, including hypothesized mediators stepwise, were used to investigate if the impact of comorbidity on overall survival is mediated by the choice of treatment or system delay.

Results

A total of 3945 patients (74.2%) underwent primary debulking surgery, whereas 1160 (21.8%) received neoadjuvant chemotherapy. When adjusting for confounders, comorbidity was not significantly associated to the choice of treatment. Surgically treated patients with moderate/severe comorbidity were more often experiencing system delay longer than required by the NCPP. No association between comorbidity and system delay was observed for patients treated with neoadjuvant chemotherapy. Survival analyses demonstrated that system delay longer than NCPP requirement positively impacts survival (hazard ratio, 0.90 [95% confidence interval, 0.82–0.98]), whereas primary treatment modality has no significant impact on survival.

Conclusions

Patients with moderate/severe comorbidity experience often a longer system delay than patients with no or mild comorbidity. Age, stage, and comorbidity are factors influencing the choice of treatment, with stage being the most important factor and comorbidity of lesser importance. The impact of comorbidity on survival does not seem to be mediated by the choice of treatment or system delay.