Decision Making in Lung Cancer – How Applicable are the Guidelines?

Causal Inference in Oncology: Why, What, How and When

Oncologists are faced with choosing the best treatment for each patient, based on the available evidence from randomized controlled trials (RCTs) and observational studies. RCTs provide estimates of the average effects of treatments on groups of patients, but they may not apply in many real-world scenarios where for example patients have different characteristics than the RCT participants, or where different treatment variants are considered. Causal inference defines what a treatment effect is and how it may be estimated with RCTs or outside of RCTs with observational - or 'real-world' - data. In this review, we introduce the field of causal inference, explain what a treatment effect is and what important challenges are with treatment effect estimation with observational data. We then provide a framework for conducting causal inference studies and describe when in oncology causal inference from observational data may be particularly valuable. Recognizing the strengths and limitations of both RCTs and observational causal inference provides a way for more informed and individualized treatment decision-making in oncology.

Radiotherapy protocol compliance in routine clinical practice for patients with stages I-III non-small-cell lung cancer

INTRODUCTION

Despite the availability of radiotherapy treatment protocols for lung cancer, considerable treatment variation occurs in clinical practice. This study assessed compliance with a radiotherapy protocol for the treatment of patients with stages I-III non-small-cell lung cancer (NSCLC) in routine clinical practice and to identify factors that were associated with compliance.

METHODS

The Cancer Institute New South Wales eviQ treatment protocol for external beam radiotherapy of stages I-III NSCLC was taken as the reference to measure compliance. All inoperable patients with stages I-III NSCLC and documented ECOG performance status treated with radiotherapy between 2007 and 2019 at two radiotherapy facilities were available for analysis. Protocol compliance rates were calculated. Univariate and multivariate logistic regression models with 23 input factors were used to determine factors significantly associated with compliance. Survival analysis was conducted for both compliant and non-compliant treatments.

RESULTS

Overall, 656 patients met the inclusion criteria. Protocol compliance was 16%. Alternative dose/fractionation was responsible for 49% of non-compliant treatments with 30% receiving an alternative curative fractionation. Five of 23 factors (age at the start of radiotherapy, stage group, ECOG performance status, tumour location and alcoholism history) showed significant associations with protocol compliance on multivariate analysis. There was no significant difference in median survival between patients receiving protocol compliant treatment (15.1 months) and non-compliant treatment (15.6 months).

CONCLUSION

Adherence to the eviQ curative radiotherapy protocol for stages I-III NSCLC was low. Alternative dose/fractionation schemes were the main reason for non-compliance. Protocol compliance was not associated with outcome.

Challenges and perspectives in use of artificial intelligence to support treatment recommendations in clinical oncology

Artificial intelligence (AI) promises to be the next revolutionary step in modern society. Yet, its role in all fields of industry and science need to be determined. One very promising field is represented by AI-based decision-making tools in clinical oncology leading to more comprehensive, personalized therapy approaches. In this review, the authors provide an overview on all relevant technical applications of AI in oncology, which are required to understand the future challenges and realistic perspectives for decision-making tools. In recent years, various applications of AI in medicine have been developed focusing on the analysis of radiological and pathological images. AI applications encompass large amounts of complex data supporting clinical decision-making and reducing errors by objectively quantifying all aspects of the data collected. In clinical oncology, almost all patients receive a treatment recommendation in a multidisciplinary cancer conference at the beginning and during their treatment periods. These highly complex decisions are based on a large amount of information (of the patients and of the various treatment options), which need to be analyzed and correctly classified in a short time. In this review, the authors describe the technical and medical requirements of AI to address these scientific challenges in a multidisciplinary manner. Major challenges in the use of AI in oncology and decision-making tools are data security, data representation, and explainability of AI-based outcome predictions, in particular for decision-making processes in multidisciplinary cancer conferences. Finally, limitations and potential solutions are described and compared for current and future research attempts.

Utilisation of radiotherapy in lung cancer: A scoping narrative literature review with a focus on the introduction of evidence-based therapeutic approaches in Europe

Background and purpose

The aim of this study was to review the published studies on the utilisation of radiotherapy in lung cancer (both small and non-small cell lung cancer, SCLC and NSCLC) patients in European countries with a population-based perspective.

Material and methods

A literature search since January 2000 until December 2022 was carried out. Only English-published papers were included, and only European data was considered. PRISMA guidelines were followed. A scoping narrative review was undertaken due to the hetereogeneity of the published papers.

Results

38 papers were included in the analysis, with the majority from the Netherlands (52.6%) and the UK (18.4%). Large variability is observed in the reported radiotherapy utilisation, around 40% for NSCLC in general and between 26 and 42% in stage I NSCLC. Stereotactic body radiotherapy (SBRT) shows a wide range of utilisation across countries and over time, from 8 to 63%. Similary, in stage III lung cancer, chemoradiotherapy (CRT) utilisation varied considerably (11-70%). Eleven studies compared radiotherapy utilisation between older and younger age-groups, showing that younger patients receive more CRT, while the opposite applies for SBRT. An widespreadlack of data on relevant covariates such as comorbidty and health-services related variables is observed.

Conclusion

The actual utilisation of radiotherapy for lung cancer reported in patterns-of-care studies (POCs) is notably lower than the evidence-based optimal utilisation. Important variability is observed by country, time period, stage at diagnosis and age. A wider use of POCs should be promoted to improve our knowledge on the actual application of evidence-based treatment recommendations.

Guideline adherence and implementation of tumor board therapy recommendations for patients with gastrointestinal cancer

PURPOSE

Although participation in multidisciplinary tumor boards (MTBs) is an obligatory quality criterion for certification, there is scarce evidence, whether MTB recommendations are consistent with consensus guidelines and whether they are followed in clinical practice. Reasons of guideline and tumor board deviations are poorly understood so far.

METHODS

MTB's recommendations from the weekly MTB for gastrointestinal cancers at the University Cancer Center Leipzig/Germany (UCCL) in 2020 were analyzed for their adherence to therapy recommendations as stated in National German guidelines and implementation within an observation period of 3 months. To assess adherence, an objective classification system was developed assigning a degree of guideline and tumor board adherence to each MTB case. For cases with deviations, underlying causes and influencing factors were investigated and categorized.

RESULTS

76% of MTBs were fully adherent to guidelines, with 16% showing deviations, mainly due to study inclusions and patient comorbidities. Guideline adherence in 8% of case discussions could not be determined, especially because there was no underlying guideline recommendation for the specific topic. Full implementation of the MTBs treatment recommendation occurred in 64% of all cases, while 21% showed deviations with primarily reasons of comorbidities and differing patient wishes. Significantly lower guideline and tumor board adherences were demonstrated in patients with reduced performance status (ECOG-PS ≥ 2) and for palliative intended therapy (p = 0.002/0.007).

CONCLUSIONS

The assessment of guideline deviations and adherence to MTB decisions by a systematic and objective quality assessment tool could become a meaningful quality criterion for cancer centers in Germany.

Individual treatment effect estimation in the presence of unobserved confounding using proxies: a cohort study in stage III non-small cell lung cancer

Randomized Controlled Trials (RCT) are the gold standard for estimating treatment effects but some important situations in cancer care require treatment effect estimates from observational data. We developed “Proxy based individual treatment effect modeling in cancer” (PROTECT) to estimate treatment effects from observational data when there are unobserved confounders, but proxy measurements of these confounders exist. We identified an unobserved confounder in observational cancer research: overall fitness. Proxy measurements of overall fitness exist like performance score, but the fitness as observed by the treating physician is unavailable for research. PROTECT reconstructs the distribution of the unobserved confounder based on these proxy measurements to estimate the treatment effect. PROTECT was applied to an observational cohort of 504 stage III non-small cell lung cancer (NSCLC) patients, treated with concurrent chemoradiation or sequential chemoradiation. Whereas conventional confounding adjustment methods seemed to overestimate the treatment effect, PROTECT provided credible treatment effect estimates.

Surgical Outcomes of Non-Small Cell Lung Cancer in Single-Zone N2 in the Aortopulmonary Zone

OBJECTIVES

 We evaluate the surgical outcome of clinically single-zone N2 lung cancer limited to aortopulmonary zone (AP zone; lymph node #5 or #6).

PATIENTS AND METHODS

 We performed a retrospective analysis of patients with non-small cell lung cancer, in whom mediastinal lymph node metastasis was confined to AP zone.

RESULTS

 A total of 84 patients who underwent upfront surgery were included in final analysis. Among these patients, pathological nodal outcomes were pN0-1 in 27 patients (32.1%), pN2a in 31 (36.9%), and pN2b in 26 (31.0%). In multivariate analysis, adenocarcinoma (p = 0.005) and staging workup without endobronchial ultrasound-transbronchial needle aspiration (p = 0.002) were independent risk factors for unexpected pN2b. The 5-year overall survival (OS) and disease-free survival (DFS) were 55.9 and 54.4%, respectively. There was no survival difference among patients with pN0-1, pN2a, and pN2b (p = 0.717). In survival analysis, there were no significant risk factors for OS. However, female sex and the ratio of positive lymph nodes to removed lymph nodes were significant risk factors for DFS in multivariate analysis (p = 0.032 and p = 0.009).

CONCLUSION

 In this study, cN2a in the AP zone with current diagnostic tool exhibited a relatively high false-positive rate (cN2/pN0-1; 32.1%). However, despite the possibility of pN2b, there were no significant differences in survival outcome according to the pathologic nodal stage.

A Multidisciplinary Lung Cancer Program: Does It Reduce Delay Between Diagnosis and Treatment?

INTRODUCTION

Lung cancer is the leading cause of cancer death in the USA, claiming more than 140,000 deaths annually. Delays in diagnosis and treatment can lead to missed opportunities for both curative and life prolonging therapies. This study aimed to evaluate duration of time to diagnosis and first treatment, as well as investigate reasons for delays in care.

METHODS

This retrospective study included all lung cancer cases diagnosed by Stony Brook's Lung Cancer Evaluation Center (LCEC) between 2013 and 2019. Demographic, radiologic, pathologic and clinical variables were investigated, including cancer staging, histology, and medical and family histories. Evaluations included the determination of median time from initial encounter to diagnosis, median time from diagnosis to start of treatment and an exploration of the factors that influence possible causes for delays in care.

RESULTS

The LCEC's comprehensive multidisciplinary lung nodule program yielded a median length of time from CT to PET of 11 days, PET to procedure of 13 days, procedure to treatment consult of 9 days, and from consult to treatment of 9 days. LCEC patients experienced an overall median of 44 days from initial presentation to first treatment compared to the national ideal of 62 days, thereby representing a 29% reduction in time from first CT to onset of treatment.

CONCLUSION

Delays in lung cancer diagnosis and treatment can negatively impact patient morbidity and mortality. This study suggests that a coordinated multidisciplinary lung cancer program may reduce delays in care, thereby improving patient outcomes.

Survival After Stereotactic Body Radiation Therapy for Clinically Diagnosed or Biopsy-Proven Early-Stage NSCLC: A Systematic Review and Meta-Analysis

INTRODUCTION

Stereotactic body radiation therapy (SBRT) is a promising curative treatment for early-stage NSCLC. It is unclear if survival outcomes for SBRT are influenced by a lack of pathological confirmation of malignancy and staging of disease in these patients. In this systematic review and meta-analysis, we assess survival outcomes after SBRT in studies with patients with clinically diagnosed versus biopsy-proven early-stage NSCLC.

METHODS

The main databases were searched for trials and cohort studies without restrictions to publication status or language. Two independent researchers performed the screening and selection of eligible studies. Outcomes were overall survival, cancer-specific survival, and disease-free survival. The inverse variance method and the random effects method for meta-analysis were used to assess pooled survival estimates.

RESULTS

A total of 11,195 nonduplicate records were identified by the original search strategy. After screening by title and abstract, 1051 potentially eligible records were identified. A total of 43 articles were included. The comparative studies showed lower 3-year overall survival and lower 2-year and 5-year cancer-specific survival for biopsy-proven disease compared to clinical disease. However, 5-year overall survival was the same for both groups. For the pooled estimates, 3-year disease-free survival and 2-year cancer-specific survival were lower for biopsied disease.

CONCLUSIONS

Results of this systematic review and meta-analysis show a discrepancy in oncological outcomes for patients undergoing SBRT for suspected early-stage NSCLC in whom there is pathologic conformation of malignancy and those who there is only a clinical diagnose of NSCLC. These results emphasize the importance of obtaining pathologic proof of malignancy.

Radiotherapy patterns of care for stage I and II non-small cell lung cancer in Sydney, Australia

INTRODUCTION

Curative radiotherapy is guideline treatment for inoperable patients of good performance status with Stage I & II Non-Small Cell Lung Cancer (NSCLC). The aim of this study was to evaluate radiotherapy patterns of care in these patients, the reasons for palliative treatment and the proportion of patients suitable for curative stereotactic ablative body radiotherapy (SABR).

METHODS

Electronic oncology databases at three institutions were queried to retrieve data on patients with inoperable Stage I & II NSCLC seen in radiation oncology clinics between 1/1/2008 and 31/12/2014. Suitability for SABR was defined as peripheral tumours less than 5 cm in size. Factors associated with curative treatment were determined using univariate and multivariate analyses.

RESULTS

Three-hundred-and-twelve patients were identified of whom 178 (57%) received curative radiotherapy, 58 (19%) palliative radiotherapy and 76 (24%) no radiotherapy. The main reason for receiving palliative rather than curative treatment was COPD or poor pulmonary function (26%). Method of diagnosis (P = 0.031), Simplified Comorbidity Score (P = 0.003), ECOG performance status (P = 0.016), FEV1% (P = 0.040), treating institution (P < 0.0001) and time period (P = 0.016) were associated with curative radiotherapy on multivariate analysis. In patients with T1-2N0M0 NSCLC, 19 (31%) who did not receive treatment and 7 (21%) who underwent palliative radiotherapy were technically and clinically suitable for SABR.

CONCLUSION

Only 57% of patients with Stage I-II NSCLC were treated with curative radiotherapy. Patient factors were the predominant reason for palliative treatment, however, treating institution also played a role. A considerable proportion of patients who underwent palliative or no radiotherapy were suitable for SABR treatment.

Prediction of 90 Day and Overall Survival after Chemoradiotherapy for Lung Cancer: Role of Performance Status and Body Composition

AIMS

If appropriate patients are to be selected for lung cancer treatment, an understanding of who is most at risk of adverse outcomes after treatment is needed. The aim of the present study was to identify predictive factors for 30 and 90 day mortality after chemoradiotherapy (CRT), and factors that were prognostic for overall survival.

MATERIALS AND METHODS

A retrospective cohort study of 194 patients with lung cancer who had undergone CRT in South East Scotland from 2008 to 2010 was undertaken. Gender, age, cancer characteristics, weight loss, body mass index (BMI), performance status (Eastern Cooperative Oncology Group; ECOG) and computed tomography-derived body composition variables were examined for prognostic significance using Cox's proportional hazards model and logistic regression.

RESULTS

The median overall survival was 19 months (95% confidence interval 16.3, 21.7). Four of 194 patients died within 30 days of treatment completion, for which there were no independent predictive variables; 22/194 (11%) died within 90 days of treatment completion. BMI < 20 and ECOG performance status ≥2 were independent predictors of death within 90 days of treatment completion (P = 0.001 and P = 0.004, respectively). Patients with either BMI < 20 or ECOG performance status ≥ 2 had an odds ratio of death within 90 days of 5.97 (95% confidence interval 2.20, 16.19), rising to an odds ratio of 13.27 (1.70, 103.47) for patients with both BMI < 20 and ECOG performance status ≥ 2. Patients with low muscle attenuation had significantly reduced overall survival (P = 0.004); individuals with low muscle attenuation had a median survival of 15.2 months (95% confidence interval 12.7, 17.7) compared with 23.0 months (95% confidence interval 18.3, 27.8) for those with high muscle attenuation, equating to a hazard ratio of death of 1.62 (95% confidence interval 1.17, 2.23, P = 0.003).

CONCLUSION

Poor performance status, low BMI and low muscle attenuation identify patients at increased risk of premature death after CRT. Risk factors for adverse outcomes should inform personalised discussions with patients about the potential harms as well as the intended benefits of treatment.

Strategies for Translating Evidence-Based Medicine in Lung Cancer into Community Practice

The landscape of non-small cell lung cancer (NSCLC) treatment has rapidly evolved over the past decade. This is exemplified by the use of molecular targeted agents, immunotherapies, and newer technologies such as stereotactic body radiotherapy (SBRT). As the translation of preclinical discoveries into clinical practice continues, the effective dissemination and implementation of evidence-based treatment of NSCLC will remain a foremost challenge for oncologists. To further extend evidence-based medicine into the community setting, community oncologists are being engaged on multiple fronts including leadership and participation in national clinical trials and utilization of internet-based resources.

Medical complexity and time to lung cancer treatment - a three-year retrospective chart review

Background

The time from a referral for suspected lung cancer is received at a hospital until treatment start has been defined as a quality indicator. Current Norwegian recommendation is that ≥70% should start surgery or radiotherapy within 42 calendar days and systemic therapy within 35 days. However, delays can occur due to medical complexity. The aim of this study was to quantify the proportion of patients who started treatment within the recommended timeframes; and to assess the proportion of non-complex patients for which there were no good reasons for delays.

Methods

We performed a retrospective chart review of all patients diagnosed with lung cancer at a university hospital during 2011–2013. We defined “non-complex” patients as those who underwent ≤1 tissue diagnostic procedure and had no delays due to comorbidity, intercurrent disease or complications to diagnostic procedures (“Medical delays”) of more than three days.

Results

Four hundred forty-nine cases were analyzed; 142 (32%) had >1 tissue diagnostic procedures; 67 (15%) had medical delays >3 days; 262 (58%) were non-complex and 363 (81%) received treatment for lung cancer. Median number of days until surgery or radiotherapy was 48 (overall) and 41 (non-complex patients). The proportions who started surgery or radiotherapy within 42 days were 41% (overall) and 56% (non-complex). Corresponding numbers for systemic therapy were 29 days (overall) and 25 days (non-complex), and 64% (overall) and 80% (non-complex).

Conclusion

Fewer lung cancer patients than desired started treatment within the recommended timeframes. Even among the least complex patients, too few patients received timely treatment. The reasons need to be identified and understood, and changes in the organization appear to be necessary in order to offer timely treatment to more patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1952-y) contains supplementary material, which is available to authorized users.

A Population-based Model of Local Control and Survival Benefit of Radiotherapy for Lung Cancer

AIMS

To estimate the population-based locoregional control and overall survival benefits of radiotherapy for lung cancer if the whole population were treated according to evidence-based guidelines. These estimates were based on a published radiotherapy utilisation (RTU) model that has been used to estimate the demand and planning of radiotherapy services nationally and internationally.

MATERIALS AND METHODS

The lung cancer RTU model was extended to incorporate an estimate of benefits of radiotherapy alone, and of radiotherapy in conjunction with concurrent chemotherapy (CRT). Benefits were defined as the proportional gains in locoregional control and overall survival from radiotherapy over no radiotherapy for radical indications, and from postoperative radiotherapy over surgery alone for adjuvant indications. A literature review (1990-2015) was conducted to identify benefit estimates of individual radiotherapy indications and summed to estimate the population-based gains for these outcomes. Model robustness was tested through univariate and multivariate sensitivity analyses.

RESULTS

If evidence-based radiotherapy recommendations are followed for the whole lung cancer population, the model estimated that radiotherapy alone would result in a gain of 8.3% (95% confidence interval 7.4-9.2%) in 5 year locoregional control, 11.4% (10.8-12.0%) in 2 year overall survival and 4.0% (3.6-4.4%) in 5 year overall survival. For the use of CRT over radiotherapy alone, estimated benefits would be: locoregional control 1.7% (0.8-2.4%), 2 year overall survival 1.7% (0.5-2.8%) and 5 year overall survival 1.2% (0.7-1.9%).

CONCLUSIONS

The model provided estimates of radiotherapy benefit that could be achieved if treatment guidelines are followed for all cancer patients. These can be used as a benchmark so that the effects of a shortfall in the utilisation of radiotherapy can be better understood and addressed. The model can be adapted to other populations with known epidemiological parameters to ensure the planning of equitable radiotherapy services.