Effect of delays on survival in patients with lung cancer

The effect of comorbidities on diagnostic interval for lung cancer in England: a cohort study using electronic health record data

BACKGROUND

Comorbid conditions may delay lung cancer diagnosis by placing demand on general practioners' time reducing the possibility of prompt cancer investigation ("competing demand conditions"), or by offering a plausible non-cancer explanation for signs/symptoms ("alternative explanation conditions").

METHOD

Patients in England born before 1955 and diagnosed with incident lung cancer between 1990 and 2019 were identified in the Clinical Practice Research Datalink and linked hospital admission and cancer registry data. Diagnostic interval was defined as time from first presentation in primary care with a relevant sign/symptom to the diagnosis date. 14 comorbidities were classified as ten "competing demand" and four "alternative explanation" conditions. Associations with diagnostic interval were investigated using multivariable linear regression models.

RESULTS

Complete data were available for 11870 lung cancer patients. In adjusted analyses diagnostic interval was longer for patients with "alternative explanation" conditions, by 31 and 74 days in patients with one and ≥2 conditions respectively versus those with none. Number of "competing demand" conditions did not remain in the final adjusted regression model for diagnostic interval.

CONCLUSIONS

Conditions offering alternative explanations for lung cancer symptoms are associated with increased diagnostic intervals. Clinical guidelines should incorporate the impact of alternative and competing causes upon delayed diagnosis.

Analysis of Diagnostic Delay and its Impact on Lung Cancer Survival: Results From the Spanish Thoracic Tumor Registry

BACKGROUND

Early detection is crucial to improve lung cancer survival rates. Delays in diagnosis might negatively impact the prognosis of the disease. This study aims to analyze the diagnostic delay in lung cancer patients and describe if there is an association between delay and survival.

METHODS

The data source used was the Thoracic Tumor Registry of the Spanish Lung Cancer Group. This analysis was restricted to lung cancer cases with information on the first date of consultation by symptoms and date of diagnosis. The delay was calculated as the number of days between the two dates. A descriptive analysis was performed, and ordinal logistic regressions were fitted with delay as the dependent variable. Kaplan-Meier survival analysis and Cox regression were performed.

RESULTS

22,755 lung cancer cases were included. Never smokers were 1.16 (95%CI: 1.06-1.27) times more likely to register longer delay than smokers. Stage 0-I-II cases had a 3.09 (95%CI: 2.88-3.32) higher risk of longer delay compared to III-IV stages. Overall, 5-year survival rate after diagnosis was 23.64% (95%CI: 22.88-24.41). In those categorized as having the shortest delay 5-year survival was 17.67% (95%CI: 16.31-19.07) and in the extreme delay it was 32.98% (95%CI: 31.28-34.69) (p<0.001). Adjusted mortality risk was higher in those with the shortest delay (HR 1.36, CI95%: 1.30-1.43) in comparison with the extreme delay.

CONCLUSIONS

Diagnostic delay is short among Spanish lung cancer patients, indicating a relatively quick diagnostic process. Extreme delays appear to be associated with higher survival rates, possibly attributed to slow-growing tumors, earlier stage at diagnosis or basically the natural history of this disease.

Survival outcomes and predicting intracranial metastasis in stage III non-small cell lung cancer treated with definitive chemoradiation: Real-world data from a tertiary cancer center

PURPOSE/OBJECTIVE

Around 30% of patients with non-small cell lung cancers (NSCLC) are diagnosed with stage III disease at presentation, of which about 50% are treated with definitive chemoradiation (CRT). Around 65-80% of patients will eventually develop intracranial metastases (IM), though associated risk factors are not clearly described. We report survival outcomes and risk factors for development of IM in a cohort of patients with stage III NSCLC treated with CRT at a tertiary cancer center.

MATERIALS/METHODS

We identified 195 patients with stage III NSCLC treated with CRT from January 2010 to May 2021. Multivariable logistic regression was used to generate odds ratios for covariates associated with development of IM. Kaplan-Meier analysis with the Log Rank test was used for unadjusted time-to-event analyses. P-value for statistical significance was set at < 0.05 with a two-sided test.

RESULTS

Out of 195 patients, 108 (55.4%) had stage IIIA disease and 103 (52.8%) had adenocarcinoma histology. The median age and follow-up (in months) was 67 (IQR 60-74) and 21 (IQR 12-43), respectively. The dose of radiation was 60 Gy in 30 fractions for148 patients (75.9%). Of the 77 patients who received treatment since immunotherapy was available and standard at our cancer center, 45 (58.4%) received at least one cycle. During follow-up, 84 patients (43.1%) developed any metastasis, and 33 (16.9%) developed IM (either alone or with extracranial metastasis). 150 patients (76.9%) experienced a treatment delay (interval between diagnosis and treatment > 4 weeks). Factors associated with developing any metastasis included higher overall stage at diagnosis (p = 0.013) and higher prescribed dose (p = 0.022). Factors associated with developing IM included higher ratio of involved over sampled lymph nodes (p = 0.001) and receipt of pre-CRT systemic or radiotherapy for any reason (p = 0.034). On multivariate logistical regression, treatment delay (OR 3.9, p = 0.036) and overall stage at diagnosis (IIIA vs. IIIB/IIIC) (OR 2.8, p = 0.02) predicted development of IM. These findings were sustained on sensitivity analysis using different delay intervals. Median OS was not reached for the overall cohort, and was 43.1 months for patients with IM and 40.3 months in those with extracranial-only metastasis (p = 0.968). In patients with any metastasis, median OS was longer (p = 0.003) for those who experienced a treatment delay (48.4 months) compared to those that did not (12.2 months), likely due to expedited diagnosis and treatment in patients with a higher symptom burden secondary to more advanced disease.

CONCLUSIONS

In patients with stage III NSCLC treated with definitive CRT, the risk of IM appears to increase with overall stage at diagnosis and, importantly, may be associated with experiencing a treatment delay (> 4 weeks). Metastatic disease of any kind remains the primary life-limiting prognostic factor in these patients with advanced lung cancer. In patients with metastatic disease, treatment delay was associated with better survival. Patients who experience a treatment delay and those initially diagnosed at a more advanced overall stage may warrant more frequent surveillance for early diagnosis and treatment of IM. Healthcare system stakeholders should strive to mitigate treatment delay in patients with locally NSCLC to reduce the risk of IM. Further research is needed to better understand factors associated with survival, treatment delay, and the development of IM after CRT in the immunotherapy era.

European Respiratory Society guideline on various aspects of quality in lung cancer care

This European Respiratory Society guideline is dedicated to the provision of good quality recommendations in lung cancer care. All the clinical recommendations contained were based on a comprehensive systematic review and evidence syntheses based on eight PICO (Patients, Intervention, Comparison, Outcomes) questions. The evidence was appraised in compliance with the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Evidence profiles and the GRADE Evidence to Decision frameworks were used to summarise results and to make the decision-making process transparent. A multidisciplinary Task Force panel of lung cancer experts formulated and consented the clinical recommendations following thorough discussions of the systematic review results. In particular, we have made recommendations relating to the following quality improvement measures deemed applicable to routine lung cancer care: 1) avoidance of delay in the diagnostic and therapeutic period, 2) integration of multidisciplinary teams and multidisciplinary consultations, 3) implementation of and adherence to lung cancer guidelines, 4) benefit of higher institutional/individual volume and advanced specialisation in lung cancer surgery and other procedures, 5) need for pathological confirmation of lesions in patients with pulmonary lesions and suspected lung cancer, and histological subtyping and molecular characterisation for actionable targets or response to treatment of confirmed lung cancers, 6) added value of early integration of palliative care teams or specialists, 7) advantage of integrating specific quality improvement measures, and 8) benefit of using patient decision tools. These recommendations should be reconsidered and updated, as appropriate, as new evidence becomes available.

Machine learning predicts the prognosis of breast cancer patients with initial bone metastases

Background

Bone is the most common metastatic site of patients with advanced breast cancer and the survival time is their primary concern; however, we lack accurate predictive models in clinical practice. In addition to this, primary surgery for breast cancer patients with bone metastases is still controversial.

Method

The data used for analysis in this study were obtained from the SEER database (2010-2019). We made a COX regression analysis to identify prognostic factors of patients with bone metastatic breast cancer (BMBC). Through cross-validation, we constructed an XGBoost model to predicting survival in patients with BMBC. We also investigated the prognosis of patients treated with neoadjuvant chemotherapy plus surgical and chemotherapy alone using propensity score matching and K-M survival analysis.

Results

Our validation results showed that the model has high sensitivity, specificity, and correctness, and it is the most accurate one to predict the survival of patients with BMBC (1-year AUC = 0.818, 3-year AUC = 0.798, and 5-year survival AUC = 0.791). The sensitivity of the 1-year model was higher (0.79), while the specificity of the 5-year model was higher (0.86). Interestingly, we found that if the time from diagnosis to therapy was ≥1 month, patients with BMBC had even better survival than those who started treatment immediately (HR = 0.920, 95%CI 0.869-0.974, P < 0.01). The BMBC patients with an income of more than USD$70,000 had better OS (HR = 0.814, 95%CI 0.745-0.890, P < 0.001) and BCSS (HR = 0.808 95%CI 0.735-0.889, P < 0.001) than who with income of < USD$50,000. We also found that compared with chemotherapy alone, neoadjuvant chemotherapy plus surgical treatment significantly improved OS and BCSS in all molecular subtypes of patients with BMBC, while only the patients with bone metastases only, bone and liver metastases, bone and lung metastases could benefit from neoadjuvant chemotherapy plus surgical treatment.

Conclusion

We constructed an AI model to provide a quantitative method to predict the survival of patients with BMBC, and our validation results indicate that this model should be highly reproducible in a similar patient population. We also identified potential prognostic factors for patients with BMBC and suggested that primary surgery followed by neoadjuvant chemotherapy might increase survival in a selected subgroup of patients.

Impact of time-to-treatment on survival for advanced non-small cell lung cancer patients in the Netherlands: a nationwide observational cohort study

BACKGROUND

The assumption that more rapid treatment improves survival of advanced non-small cell lung cancer (NSCLC) has not yet been proven. We studied the relation between time-to-treatment and survival in advanced stage NSCLC patients in a large multicentric nationwide retrospective cohort. Additionally, we identified factors associated with delay.

METHOD

We selected 10 306 patients, diagnosed and treated between 2014 and 2019 for clinical stage III and IV NSCLC, from the Netherlands Cancer Registry that includes nationwide data from 109 Dutch hospitals. Associations between survival and time-to-treatment were tested with Cox proportional hazard regression analyses. Time-to-treatment was adjusted for multiple covariates including diagnostic procedures and type of therapy. Factors associated with delay were identified by multilevel logistic regression.

RESULTS

Risk of death significantly decreased with longer time-to-treatment for stage III patients receiving only radiotherapy (adjusted HR, aHR >21 days: 0.59 (95% CI 0.48 to 0.73)) or any type of systemic therapy (aHR >49 days: 0.72 (95% CI 0.56 to 0.91)) and stage IV patients receiving chemotherapy and/or immunotherapy (aHR >21 days: 0.81 (95% CI 0.73 to 0.88)). No significant association was found for stage III patients treated with chemoradiotherapy and stage IV patients treated with targeted therapy. More complex diagnostic procedures often delay treatment.

CONCLUSION

Although in general it is important to start treatment as early as possible, our study finds no evidence that a more rapid start of treatment improves outcomes in advanced stage NSCLC patients. The benefit of urgent treatment is probably confounded by unmeasured patient and tumour characteristics and, clinical urgency dictating timelines of treatment. Time-to-treatment and its impact should be continuously evaluated as therapeutic strategies continue to evolve and improve.

Clinical impact of delays in the management of lung cancer patients in the last decade: systematic review

INTRODUCTION

Due to the importance of lung cancer early treatment because of its severity and extent worldwide a systematic literature review was conducted about the impact of delays in waiting times on the disease prognosis.

MATERIALS AND METHODS

We conducted a systematic search of observational studies (2010-2020) including adult patients diagnosed with lung cancer and reporting healthcare timelines and their clinical consequences.

RESULTS

We included 38 articles containing data on waiting times and prognosis; only 31 articles linked this forecast to a specific waiting time. We identified 41 healthcare time intervals and found medians of 6-121 days from diagnosis to treatment and 4-19.5 days from primary care to specialist visit: 37.5% of the intervals indicated better prognosis with longer waiting times.

CONCLUSIONS

All articles emphasized that waiting times must be reduced to achieve good management and prognosis of lung cancer. Further prospective studies are needed on the relationship between waiting times and prognosis of lung cancer.

Therapeutic Underuse and Delay in Hepatocellular Carcinoma: Prevalence, Associated Factors, and Clinical Impact

Prognosis of hepatocellular carcinoma (HCC) could be affected by lack of or delayed therapy. We aimed to characterize the prevalence, correlates, and clinical impact of therapeutic underuse and delay in patients with HCC. Patients with HCC diagnosed between 2010 and 2017 were analyzed from the United States National Cancer Database. Logistic regression analysis identified factors associated with no and delayed (>90 days after diagnosis) HCC treatment. Cox proportional hazards regression with landmark analysis assessed the association between therapeutic delay and overall survival (OS), accounting for immortal time bias. Of 116,299 patients with HCC, 24.2% received no treatment and 18.4% of treated patients had delayed treatment. Older age, Black, Hispanic, lower socioeconomic status, earlier year of diagnosis, treatment at nonacademic centers, Northeast region, increased medical comorbidity, worse liver dysfunction, and higher tumor burden were associated with no treatment. Among treated patients, younger age, Hispanic, Black, treatment at academic centers, West region, earlier tumor stage, and receipt of noncurative treatment were associated with treatment delays. In multivariable Cox regression with a landmark of 150 days, patients with and without treatment delays had similar OS (adjusted hazard ratio [aHR], 1.01; 95% confidence interval [CI], 0.98‐1.04) with a median survival of 33.7 vs. 32.1 months, respectively. However, therapeutic delay was associated with worse OS in patients who had tumor, nodes, and metastases (TNM) stage 1 (aHR, 1.06; 95% CI, 1.01‐1.11) or received curative treatment (aHR, 1.12; 95% CI, 1.05‐1.18). Conclusion: One‐fourth of patients with HCC receive no therapy and one‐fifth of treated patients experience treatment delays. Both were associated with demographic, socioeconomic, and clinical characteristics of patients as well as facility type and region. The association between therapeutic delay and survival was stage and treatment dependent.

Importance of diagnosis-to-treatment interval in newly diagnosed patients with diffuse large B-cell lymphoma

Treatment of patients with malignancy sometimes be delayed due to various reasons. Several studies revealed that an influence of diagnosis-to-treatment interval (DTI) on outcomes differs depending on the type of malignancy. In this study, we evaluated the influence of DTI on clinical outcomes in newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL). A total of 199 patients were identified with a median DTI of 22 days. At 2 years, patients with short DTI (0–22 days) showed significantly poorer OS (62.7% vs 86.4%) and PFS (55.1% vs 75.9%) compared to those with long DTI (over 22 days). Although short DTI was strongly correlated with several known adverse factors, it remained to be an independent prognostic factor by multivariate analysis. In conclusion, our study confirmed the importance of DTI in patients with DLBCL. Researchers should consider DTI as one of the important prognostic factors and plan clinical trials to be able to enroll patients with aggressive disease requiring urgent treatment.

Cancer diagnostic tools to aid decision-making in primary care: mixed-methods systematic reviews and cost-effectiveness analysis

BACKGROUND

Tools based on diagnostic prediction models are available to help general practitioners diagnose cancer. It is unclear whether or not tools expedite diagnosis or affect patient quality of life and/or survival.

OBJECTIVES

The objectives were to evaluate the evidence on the validation, clinical effectiveness, cost-effectiveness, and availability and use of cancer diagnostic tools in primary care.

METHODS

Two systematic reviews were conducted to examine the clinical effectiveness (review 1) and the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general practitioners in cancer diagnosis. Bibliographic searches were conducted on MEDLINE, MEDLINE In-Process, EMBASE, Cochrane Library and Web of Science) in May 2017, with updated searches conducted in November 2018. A decision-analytic model explored the tools' clinical effectiveness and cost-effectiveness in colorectal cancer. The model compared patient outcomes and costs between strategies that included the use of the tools and those that did not, using the NHS perspective. We surveyed 4600 general practitioners in randomly selected UK practices to determine the proportions of general practices and general practitioners with access to, and using, cancer decision support tools. Association between access to these tools and practice-level cancer diagnostic indicators was explored.

RESULTS

Systematic review 1 - five studies, of different design and quality, reporting on three diagnostic tools, were included. We found no evidence that using the tools was associated with better outcomes. Systematic review 2 - 43 studies were included, reporting on prediction models, in various stages of development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk Ltd, Leeds, UK) and risk assessment tools.

DECISION MODEL

In the absence of studies reporting their clinical outcomes, QCancer and risk assessment tools were evaluated against faecal immunochemical testing. A linked data approach was used, which translates diagnostic accuracy into time to diagnosis and treatment, and stage at diagnosis. Given the current lack of evidence, the model showed that the cost-effectiveness of diagnostic tools in colorectal cancer relies on demonstrating patient survival benefits. Sensitivity of faecal immunochemical testing and specificity of QCancer and risk assessment tools in a low-risk population were the key uncertain parameters.

SURVEY

Practitioner- and practice-level response rates were 10.3% (476/4600) and 23.3% (227/975), respectively. Cancer decision support tools were available in 83 out of 227 practices (36.6%, 95% confidence interval 30.3% to 43.1%), and were likely to be used in 38 out of 227 practices (16.7%, 95% confidence interval 12.1% to 22.2%). The mean 2-week-wait referral rate did not differ between practices that do and practices that do not have access to QCancer or risk assessment tools (mean difference of 1.8 referrals per 100,000 referrals, 95% confidence interval -6.7 to 10.3 referrals per 100,000 referrals).

LIMITATIONS

There is little good-quality evidence on the clinical effectiveness and cost-effectiveness of diagnostic tools. Many diagnostic prediction models are limited by a lack of external validation. There are limited data on current UK practice and clinical outcomes of diagnostic strategies, and there is no evidence on the quality-of-life outcomes of diagnostic results. The survey was limited by low response rates.

CONCLUSION

The evidence base on the tools is limited. Research on how general practitioners interact with the tools may help to identify barriers to implementation and uptake, and the potential for clinical effectiveness.

FUTURE WORK

Continued model validation is recommended, especially for risk assessment tools. Assessment of the tools' impact on time to diagnosis and treatment, stage at diagnosis, and health outcomes is also recommended, as is further work to understand how tools are used in general practitioner consultations.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42017068373 and CRD42017068375.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology programme and will be published in full in Health Technology Assessment; Vol. 24, No. 66. See the NIHR Journals Library website for further project information.

Lung cancer patients' journey from first symptom to treatment: Results from a Greek registry

BACKGROUND

To map the patients' journey from symptoms onset to treatment initiation for the most frequent histological types of lung cancer in Greece and describe the initial treatment that patients receive.

METHODS

The primary data source was a Greek hospital-based registry. Demographic, anthropometric, lifestyle, and diagnostic-related characteristics as well as treatment-related data were extracted from the registry for patients diagnosed with Adenocarcinoma, Squamous and Small Cell Lung Cancer (SCLC). The time intervals from symptoms onset to diagnosis (StD), diagnosis to treatment initiation (DtT), symptoms onset to treatment initiation (StT) and surgery to post-surgery treatment (SRGtT) were estimated.

RESULTS

231, 120 and 122 patients were diagnosed with Adenocarcinoma, SCLC and Squamous, respectively. The percentage of patients diagnosed at stage III/IV ranged from 75% in Adenocarcinoma to 97.5% in SCLC (p < 0.001). The median (IQR) StD was 52 (28-104) days and no difference was detected across the three histological types (p = 0.301). Cough as first symptom was the only determinant of StD (p = 0.001). The median (IQR) DtT was 23 (13-36) days, with this time interval being shorter among patients with SCLC compared to patients with Adenocarcinoma and Squamous (p < 0.001). The median (IQR) StT was 81 (51-139) days. Almost one third of patients with Adenocarcinoma and Squamous were subjected first to surgery and the median (IQR) SRGtT was 42 (34-55) days.

CONCLUSIONS

Our results indicate that time interval from symptoms onset to treatment initiation in Greece is substantially prolonged, highlighting the need for strategies to expedite lung cancer diagnosis and access to evidence-based treatment.

Surgical Delay Is Associated with Improved Survival in Hepatocellular Carcinoma: Results of the National Cancer Database

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the fastest growing causes of cancer-related death in the USA. Studies that investigated the impact of HCC therapeutic delays are limited to single centers, and no large-scale database research has been conducted. This study investigated the association of surgical delay and survival in HCC patients.

METHODS

Patients underwent local tumor destruction and hepatic resection for stages I-III HCC were identified from the 2004 to 2013 Commission on Cancer's National Cancer Database. Surgical delay was defined as > 60 days from the date of diagnosis to surgery. Generalized linear-mixed model assessed the demographic and clinical factors associated with delay, and frailty Cox proportional hazard analysis examined the prognostic factors for overall survival.

RESULTS

A total of 12,102 HCC patients met the eligibility criteria. Median wait time to surgery was 50 days (interquartile range, 29-86), and 4987 patients (41.2%) had surgical delay. Delayed patients demonstrated better 5-year survival for local tumor destruction (29.1 vs. 27.6%; P = .001) and resection (44.1 vs. 41.0%; P = .007). Risk-adjusted model indicated that delayed patients had a 7% decreased risk of death (HR, 0.93; 95% CI, 0.87-0.99; P = .027). Similar findings were also observed using other wait time cutoffs at 50, 70, 80, 90, and 100 days.

CONCLUSIONS

A plausible explanation of this finding may be case prioritization, in which patients with more severe and advanced disease who were at higher risk of death received earlier surgery, while patients with less-aggressive tumors were operated on later and received more comprehensive preoperative evaluation.

Predicting delays in lung cancer diagnosis and staging

Background

Despite growing interest in increasing the efficiency and speed of the diagnosis, staging, and treatment of lung cancer (LC), the interval from signs and symptoms to diagnosis and treatment remains longer than recommended. The aim of this study was to analyze the factors that cause delays in the LC diagnosis/staging process and, consequently, delays in making therapeutic decisions.

Methods

We analyzed audit data from a prospective dataset of 1330 patients assessed at The Lung Cancer Rapid Diagnostic Unit from 26 June 2013 to 26 March 2016. The number and type of procedures and medical tests and the times of all procedures were recorded. Clinical and epidemiological variables and whether the diagnosis was performed on an inpatient or outpatient basis were also recorded.

Results

Malignancy was confirmed in 737 (55.4%) of the 1330 patients, with LC in 627 of these (85.2%). The mean interval to final diagnosis was 19.8 ± 13.9 days. Variables significantly related to a longer diagnostic time were the number of days until computed tomography (CT) was performed (odds ratio [OR], 95% confidence interval [CI] 1.347, 1.103–1.645; P = 0.003), until a histology sample was obtained (OR 1.243, 95% CI1.062–1.454; P = 0.007), and the total number of tests performed during the diagnostic and staging process (OR 1.823, 95% CI 1.046–3.177; P = 0.03).

Conclusions

A greater number of tests and more days to CT and histology led to longer delay times. Optimization of these factors should reduce delays in the LC diagnosis process.

Time to Surgery: a Misguided Quality Metric in Early Stage Pancreatic Cancer

BACKGROUND

Longer time to surgery is associated with worse outcomes in several cancers. We sought to identify disparities in time from diagnosis to surgery in pancreatic cancer and whether delays to surgery correlated with worse survival.

METHODS

The US National Cancer Database (2003-2011) was reviewed for patients with clinical stages I-II pancreatic adenocarcinoma who underwent surgical resection. Patients who received neoadjuvant therapy were excluded. Linear regression, Kaplan-Meier analyses, and Cox regression were performed as 3-month landmark analyses.

RESULTS

Of the 14,807 patients included, 37.8% underwent resection ≤ 1 week, 13.7% 1-2 weeks, 25.4% 2-4 weeks, 19.5% 4-8 weeks, and 3.7% 8-12 weeks. Older age, Medicare coverage, greater distance from hospital, treatment at an academic center, and greater comorbidities were associated with increased time. After excluding patients treated within 1 week of diagnosis and controlling for patient, disease, and treatment characteristics, greater time was not associated with worse survival (2-4, HR 1.03, P = 0.399; 4-8, HR 0.98, P = 0.529; 8-12, P = 0.123).

CONCLUSIONS

For patients with stages I-II pancreatic adenocarcinoma, there are disparities in surgical wait times. However, earlier initiation of surgical resection within 12 weeks of diagnosis is not associated with a survival benefit. This suggests that allowing time for confirmatory testing and optimization in preparation for surgery may not negatively impact survival.

Do Moderate Surgical Treatment Delays Influence Survival in Colon Cancer?

BACKGROUND

Studies examining treatment delay and survival after surgical treatment of colon cancer have varied in quality and outcome, with little evidence available regarding the safety of longer surgical treatment wait times.

OBJECTIVE

Our study examined the effect of surgical treatment wait times on survival for patients with stage I to III colon cancer.

DESIGN

A subset cohort analysis was performed using data from a prospectively maintained database.

SETTINGS

The study was conducted at a tertiary referral center.

PATIENTS

Data on all of the patients undergoing elective surgery for stage I to III colon cancer from 2006 to 2015 were collected from a prospectively maintained clinical and administrative database.

MAIN OUTCOME MEASURES

We examined the impact of prolonged wait time to surgery on disease-free and overall survival. Patients were divided into 2 groups based on a treatment wait time of ≤30 or >30 days and were compared using a Cox proportional hazards model. A subgroup analysis was performed using alternative treatment delay cutoffs of 60 and 90 days.

RESULTS

There were 908 patients with stage I to III colon cancer treated over the study period, with a median treatment wait time of 38 days (interquartile range, 21-61 days); 368 patients were treated within 30 days, and 540 were treated beyond 30 days from diagnosis. In adjusted multivariate analysis, a treatment delay of >30 days was not associated with decreased disease-free survival (HR = 0.89 (95% CI, 0.61-1.3); p = 0.52) or overall survival (HR = 0.82 (95% CI, 0.63-1.1); p = 0.16). Likewise, subgroup analysis using alternative treatment delay cutoffs of 60 and 90 days did not demonstrate an adverse effect on survival.

LIMITATIONS

This study was limited by retrospective analysis.

CONCLUSIONS

Despite longer median treatment wait times from diagnosis to surgery, with the majority of patients exceeding 30 days and many experiencing delays of 2 to 3 months, no adverse impact on survival was observed. Patients who require additional consultations or investigations preoperatively may safely have their surgery moderately delayed to minimize their perioperative risk without any evidence that this will compromise treatment outcomes. See Video Abstract at http://links.lww.com/DCR/A397.

Waiting Time from Diagnosis to Treatment has no Impact on Survival in Patients with Esophageal Cancer

Background

Waiting time from diagnosis to treatment has emerged as an important quality indicator in cancer care. This study was designed to determine the impact of waiting time on long-term outcome of patients with esophageal cancer who are treated with neoadjuvant therapy followed by surgery or primary surgery.

Methods

Patients who underwent esophagectomy for esophageal cancer at the University Medical Center Utrecht between 2003 and 2014 were included. Patients treated with neoadjuvant therapy followed by surgery and treated with primary surgery were separately analyzed. The influence of waiting time on survival was analyzed using Cox proportional hazard analyses. Kaplan–Meier curves for short (<8 weeks) and long (≥8 weeks) waiting times were constructed.

Results

A total of 351 patients were included; 214 received neoadjuvant treatment, and 137 underwent primary surgery. In the neoadjuvant group, the waiting time had no impact on disease-free survival (DFS) [hazard ratio (HR) 0.96, 95 % confidence interval (CI) 0.88–1.04; p = 0.312] or overall survival (OS) (HR 0.96, 95 % CI 0.88–1.05; p = 0.372). Accordingly, no differences were found between neoadjuvantly treated patients with waiting times of <8 and ≥8 weeks in terms of DFS (p = 0.506) and OS (p = 0.693). In the primary surgery group, the waiting time had no impact on DFS (HR 1.03, 95 % CI 0.95–1.12; p = 0.443) or OS (HR 1.06, 95 % CI 0.99–1.13; p = 0.108). Waiting times of <8 weeks versus ≥8 weeks did not result in differences regarding DFS (p = 0.884) or OS (p = 0.374).

Conclusions

In esophageal cancer patients treated with curative intent by either neoadjuvant therapy followed by surgery or primary surgery, waiting time from diagnosis to treatment has no impact on long-term outcome.

Diagnostic intervals and its association with breast, prostate, lung and colorectal cancer survival in England: historical cohort study using the Clinical Practice Research Datalink

Rapid diagnostic pathways for cancer have been implemented, but evidence whether shorter diagnostic intervals (time from primary care presentation to diagnosis) improves survival is lacking. Using the Clinical Practice Research Datalink, we identified patients diagnosed with female breast (8,639), colorectal (5,912), lung (5,737) and prostate (1,763) cancers between 1998 and 2009, and aged >15 years. Presenting symptoms were classified as alert or non-alert, according to National Institute for Health and Care Excellence guidance. We used relative survival and excess risk modeling to determine associations between diagnostic intervals and five-year survival. The survival of patients with colorectal, lung and prostate cancer was greater in those with alert, compared with non-alert, symptoms, but findings were opposite for breast cancer. Longer diagnostic intervals were associated with lower mortality for colorectal and lung cancer patients with non-alert symptoms, (colorectal cancer: Excess Hazards Ratio, EHR >6 months vs <1 month: 0.85; 95% CI: 0.72-1.00; Lung cancer: EHR 3-6 months vs <1 month: 0.87; 95% CI: 0.80-0.95; EHR >6 months vs <1 month: 0.81; 95% CI: 0.74-0.89). Prostate cancer mortality was lower in patients with longer diagnostic intervals, regardless of type of presenting symptom. The association between diagnostic intervals and cancer survival is complex, and should take into account cancer site, tumour biology and clinical practice. Nevertheless, unnecessary delay causes patient anxiety and general practitioners should continue to refer patients with alert symptoms via the cancer pathways, and actively follow-up patients with non-alert symptoms in the community.

Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review

BACKGROUND

It is unclear whether more timely cancer diagnosis brings favourable outcomes, with much of the previous evidence, in some cancers, being equivocal. We set out to determine whether there is an association between time to diagnosis, treatment and clinical outcomes, across all cancers for symptomatic presentations.

METHODS

Systematic review of the literature and narrative synthesis.

RESULTS

We included 177 articles reporting 209 studies. These studies varied in study design, the time intervals assessed and the outcomes reported. Study quality was variable, with a small number of higher-quality studies. Heterogeneity precluded definitive findings. The cancers with more reports of an association between shorter times to diagnosis and more favourable outcomes were breast, colorectal, head and neck, testicular and melanoma.

CONCLUSIONS

This is the first review encompassing many cancer types, and we have demonstrated those cancers in which more evidence of an association between shorter times to diagnosis and more favourable outcomes exists, and where it is lacking. We believe that it is reasonable to assume that efforts to expedite the diagnosis of symptomatic cancer are likely to have benefits for patients in terms of improved survival, earlier-stage diagnosis and improved quality of life, although these benefits vary between cancers.

Delays for diagnosis and treatment of lung cancers: a systematic review

BACKGROUND AND AIMS

The impact of diagnosis and treatment delays for non-small cell lung cancer management is poorly understood, even if the literature on the subject is currently increasing in importance. We have few indicators that can serve as reference for quality assurance actions. The objective of this review was to review the literature on the subject.

METHODS

A literature search, using the words 'human lung cancer delay' and 'human lung cancer waiting time', was undertaken in Medline database.

RESULTS

Several studies analyzed these delays mostly in a monocentric setting. There is an important variability in the definition of these delays, in the collection methods and in the results obtained. However, it seems distinctly clear that long delays are frequently observed in less symptomatic patients and, therefore, are accompanied by better prognosis.

CONCLUSION

More standardized definitions and procedures to calculate time intervals between cancer diagnosis and treatment should be implemented to better understand the delays of lung cancer management.

Timeliness of care and prognosis in patients with lung cancer

BACKGROUND

Timeliness of care is an important dimension of health care quality. The determining factors of less timely care and their influence on the survival of patients with lung cancer (LC) remain uncertain.

AIMS

To analyse the delays in the diagnosis and treatment of LC in our health area, the factors associated with the timeliness of care and their possible relationship with the survival of these patients.

METHODS

A retrospective study was conducted on all patients with a cytohistologically confirmed diagnosis of LC between 1 June 2005 and 31 May 2008. The time delays for consultation (specialist delay), diagnosis (diagnosis delay), and treatment (treatment delay), were analysed, as well as the factors associated with these delays and the influence of the timeliness of care on survival.

RESULTS

A total of 307 cases were included (87 % males). The mean specialist delay was 53.6 days (median 35 days), diagnosis delay 31.5 days (median 18 days), treatment delay 23.5 days (median 14 days). The greater age of the patient and a more advanced stage were associated with a shorter specialist delay. Male sex, a more advanced stage, and poor general status were associated with a shorter treatment delay. The survival is longer in patients with a longer treatment delay.

CONCLUSIONS

The delay in the diagnosis in our population seems to be excessively long. The greater the age, a more advanced tumour stage, male sex, and poor general health status are associated with shorter delays. A longer treatment delay is associated with a longer survival.

Prognostic implications of treatment delays in the surgical resection of lung cancer

The survival of patients with lung cancer remains low in most developed countries, which is largely attributable to the advanced stage of the disease when it presents. It seems obvious that if lung cancer could be found at an earlier stage, the prognosis of patients would be improved. The evidence from the medical literature on this point is conflicting; most studies suggest that delays in diagnosis are not prognostically important. When strategies are in place to expedite the investigation of individuals suspected of having lung cancer, the stage of disease typically shifts toward earlier-stage disease and resection rates increase.

Influence of delays in diagnosis and treatment on survival in small cell lung cancer patients

The purpose of this study was to evaluate the influence on survival of delays in the diagnosis and treatment in an unselected population of small cell lung (SCLC) patients. Demographic and disease data of 3,479 SCLC patients were registered in the National Tuberculosis and Lung Diseases Research Institute in Warsaw, Poland during 1995-1998. In 50 % of patients, treatment started within 78 days from the appearance of first symptom(s). The median delay was 30 days (mean 47 days) and the median referral delay to a specialist was 19 days (mean 36 days). Half of SCLC patients were diagnosed during 34 days (mean 55 days). The mean time elapse from the diagnosis to the onset of therapy was 30 days (median 6 days). The multivariate analysis revealed that male gender-HR (hazard ratio = 1.2), ECOG Performance Status of 2 (HR = 1.5) and 3 + 4 (HR = 2.4), and clinical stage III (HR = 1.3) and IV (HR = 1.9) of the disease were independent negative predictors of survival. The patients treated with surgery and combined modality treatment had a better prognosis than those treated with chemoradiotherapy (HR = 1.6), chemotherapy (HR = 2.5), symptomatically (HR = 4.0), or those who refused therapy (HR = 3.9). The delay in the diagnosis and treatment had no effect on survival. Interestingly, patients who were diagnosed faster (below 42 days) actually had a worse prognosis than those diagnosed later. We conclude that a prolonged workup of SCLC patients and an extended time for treatment onset have a positive influence on survival, which may likely have to do with the determination of disease stage and more targeted treatment.

Implementing a Cancer Fast-track Programme between primary and specialised care in Catalonia (Spain): a mixed methods study

Background:

The Cancer Fast-track Programme's aim was to reduce the time that elapsed between well-founded suspicion of breast, colorectal and lung cancer and the start of initial treatment in Catalonia (Spain). We sought to analyse its implementation and overall effectiveness.

Methods:

A quantitative analysis of the programme was performed using data generated by the hospitals on the basis of seven fast-track monitoring indicators for the period 2006–2009. In addition, we conducted a qualitative study, based on 83 semistructured interviews with primary and specialised health professionals and health administrators, to obtain their perception of the programme's implementation.

Results:

About half of all new patients with breast, lung or colorectal cancer were diagnosed via the fast track, though the cancer detection rate declined across the period. Mean time from detection of suspected cancer in primary care to start of initial treatment was 32 days for breast, 30 for colorectal and 37 for lung cancer (2009). Professionals associated with the implementation of the programme showed that general practitioners faced with suspicion of cancer had changed their conduct with the aim of preventing lags. Furthermore, hospitals were found to have pursued three specific implementation strategies (top-down, consensus-based and participatory), which made for the cohesion and sustainability of the circuits.

Conclusion:

The programme has contributed to speeding up diagnostic assessment and treatment of patients with suspicion of cancer, and to clarifying the patient pathway between primary and specialised care.