Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing.

BACKGROUND: Patients with cancer often have unmet psychosocial needs. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This work used natural language processing to predict which patients will see a counsellor or psychiatrist from a patient's initial oncology consultation document. We believe this is the first use of artificial intelligence to predict psychiatric outcomes from non-psychiatric medical documents. METHODS: This retrospective prognostic study used data from 47,625 patients at BC Cancer. We analyzed initial oncology consultation documents using traditional and neural language models to predict whether patients would see a counsellor or psychiatrist in the 12 months following their initial oncology consultation. RESULTS: Here, we show our best models achieved a balanced accuracy (receiver-operating-characteristic area-under-curve) of 73.1% (0.824) for predicting seeing a psychiatrist, and 71.0% (0.784) for seeing a counsellor. Different words and phrases are important for predicting each outcome. CONCLUSION: These results suggest natural language processing can be used to predict psychosocial needs of patients with cancer from their initial oncology consultation document. Future research could extend this work to predict the psychosocial needs of medical patients in other settings.

Patients with cancer often need support for their mental health. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This study trained a type of artificial intelligence (AI) called natural language processing to read the consultation report an oncologist writes after they first see a patient to predict which patients will see a counsellor or psychiatrist. The AI predicted this with performance similar to other uses of AI in mental health, and used different words and phrases to predict who would see a psychiatrist compared to seeing a counsellor. We believe this is the first use of AI to predict mental health outcomes from medical documents written by clinicians outside of mental health. This study suggests this type of AI can predict the mental health needs of patients with cancer from this widely-available document.

Outcomes of patients with advanced epithelial growth factor receptor mutant lung cancer treated with first-line osimertinib who would not have met the eligibility criteria for the FLAURA clinical trial.

OBJECTIVES: Osimertinib is largely used as first-line therapy for metastatic epithelial growth factor receptor (EGFR) mutant lung cancers based on the FLAURA clinical trial. Real-world patient outcomes often differ from clinical trial outcomes. This study evaluated the efficacy of first-line osimertinib in patients treated in British Columbia (BC), Canada. Furthermore, we compared the outcomes of patients who would and would not have been eligible for the original FLAURA trial. METHODS: Consecutive patients receiving first-line osimertinib for metastatic EGFR exon19 or L858R lung cancer were identified using the BC Cancer Pharmacy Database. Patient eligibility for the FLAURA clinical trial were retrospectively reviewed based on the following criteria: ECOG ≥ 2, symptomatic brain metastases or on steroids, hemoglobin < 90 g/L, platelets < 100x109/L, or a creatinine clearance < 50 mL/min. mOS was assessed for the entire population and compared between patients who would have been eligible and ineligible for FLAURA. RESULTS: From January 2020 to October 2021, 311 patients received first-line osimertinib; 44 % (137/311) were deemed FLAURA ineligible, predominantly due to low ECOG (n = 120). After a median follow-up of 26.5 months, the mOS for the entire cohort was 27.4 months (95 %CI 23.8-30.1). The mOS for ineligible patients was 18 months shorter than eligible patients (15.8 vs 34.2, p < 0.001). Ineligible patients had higher rates of de novo stage IV disease, higher rates of stage IVB disease, and more sites of disease than eligible patients. CONCLUSION: In this real-world population, nearly half of patients would have been ineligible for FLAURA. The mOS was one year shorter than reported in FLAURA. However, patients who would have been eligible for the FLAURA clinical trial had similar OS to patients enrolled in FLAURA. Trial ineligible patients had a higher burden of disease at baseline which may have led to inferior outcomes. Further research is needed to improve outcomes in these patients.

Treating anaplastic lymphoma kinase (ALK) fusion-driven metastatic non-small cell lung cancer (NSCLC) with alectinib through pregnancy.

Management of cancer during pregnancy requires careful consideration of risks and benefits from maternal and fetal perspectives. For advanced lung adenocarcinomas, with no targetable driver mutations, there is evidence-based guidance on the use of carboplatin-paclitaxel chemotherapy after first trimester. In contrast, for epidermal growth factor receptor (EGFR)-mutated or anaplastic lymphoma kinase (ALK)-rearranged metastatic lung adenocarcinomas, there is a paucity of clinical data on the safety of EGFR and ALK tyrosine kinase inhibitors to mother and fetus for official guidelines to recommend the use of these otherwise-first-line therapies in pregnancy. Considering this knowledge gap, we present a case of a young gravida 1 para 0 (G1P0) woman who continued alectinib 300 mg oral two times per day for ALK-rearranged metastatic lung adenocarcinoma throughout all 36 weeks of her pregnancy and delivered a healthy baby at term via caesarean section (C-section).

Tensor radiomics: paradigm for systematic incorporation of multi-flavoured radiomics features.

Background: Radiomics features hold significant value as quantitative imaging biomarkers for diagnosis, prognosis, and treatment response assessment. To generate radiomics features and ultimately develop signatures, various factors can be manipulated, including image discretization parameters (e.g., bin number or size), convolutional filters, segmentation perturbation, or multi-modality fusion levels. Typically, only one set of parameters is employed, resulting in a single value or "flavour" for each radiomics feature. In contrast, we propose "tensor radiomics" (TR) where tensors of features calculated using multiple parameter combinations (i.e., flavours) are utilized to optimize the creation of radiomics signatures. Methods: We provide illustrative instances of TR implementation in positron emission tomography-computed tomography (PET-CT), magnetic resonance imaging (MRI), and CT by leveraging machine learning (ML) and deep learning (DL) methodologies, as well as reproducibility analyses: (I) to predict overall survival (OS) in lung cancer (CT) and head and neck cancer (PET-CT), TR was employed by varying bin sizes. This approach involved use of a hybrid deep neural network called 'TR-Net' and two ML-based techniques for combining different flavours. (II) TR was constructed by incorporating different segmentation perturbations and various bin sizes to classify the response of late-stage lung cancer to first-line immunotherapy using CT images. (III) In MRI of glioblastoma (GBM), TR was implemented to generate multi-flavour radiomics features, enabling enhanced analysis and interpretation. (IV) TR was employed via multiple PET-CT fusions in head and neck cancer. Flavours based on different fusions were created using Laplacian pyramids and wavelet transforms. Results: Our findings demonstrated that TR outperformed conventional radiomics features in lung cancer CT and head and neck cancer PET-CT images, significantly enhancing OS prediction accuracy. TR also improved classification of lung cancer response to therapy and exhibited notable advantages in reproducibility compared to single-flavour features in MR imaging of GBM. Moreover, in head and neck cancer, TR through multiple PET-CT fusions exhibited improved performance in predicting OS. Conclusions: We conclude that the proposed TR paradigm has significant potential to improve performance in different medical imaging tasks. By incorporating multiple flavours of radiomics features, TR overcomes limitations associated with individual features and shows promise in enhancing prognostic capabilities in clinical settings.

ctDNA response after pembrolizumab in non-small cell lung cancer: phase 2 adaptive trial results.

Circulating tumor DNA (ctDNA) has shown promise in capturing primary resistance to immunotherapy. BR.36 is a multi-center, randomized, ctDNA-directed, phase 2 trial of molecular response-adaptive immuno-chemotherapy for patients with lung cancer. In the first of two independent stages, 50 patients with advanced non-small cell lung cancer received pembrolizumab as standard of care. The primary objectives of stage 1 were to ascertain ctDNA response and determine optimal timing and concordance with radiologic Response Evaluation Criteria in Solid Tumors (RECIST) response. Secondary endpoints included the evaluation of time to ctDNA response and correlation with progression-free and overall survival. Maximal mutant allele fraction clearance at the third cycle of pembrolizumab signified molecular response (mR). The trial met its primary endpoint, with a sensitivity of ctDNA response for RECIST response of 82% (90% confidence interval (CI): 52-97%) and a specificity of 75% (90% CI: 56.5-88.5%). Median time to ctDNA response was 2.1 months (90% CI: 1.5-2.6), and patients with mR attained longer progression-free survival (5.03 months versus 2.6 months) and overall survival (not reached versus 7.23 months). These findings are incorporated into the ctDNA-driven interventional molecular response-adaptive second stage of the BR.36 trial in which patients at risk of progression are randomized to treatment intensification or continuation of therapy. ClinicalTrials.gov ID: NCT04093167 .

Real-World Clinical Outcomes for Patients with EGFR and HER2 Exon 20 Insertion-Mutated Non-Small-Cell Lung Cancer.

(1) Background: Exon 20 insertion mutations (ex20ins) in EGFR and HER2 are uncommon driver mutations in non-small-cell lung cancer (NSCLC), with a poor prognosis and few targeted therapy options, and there are limited real-world data. Here, we report the clinicopathologic features and outcomes for patients with ex20ins NSCLC across British Columbia, Canada. (2) Methods: NSCLC patients with ex20ins in EGFR or HER2 were identified via tumour testing between 1 January 2016 and 31 December 2021 (n = 7233). Data were collected by chart review. Survival analyses were performed using the Kaplan-Meier method using the log-rank test. (3) Results: A total of 131 patients were identified. The median age was 66. Thirty-three percent of patients had brain metastases. For the EGFR cohort, the median OS was 18.6 months for patients who received any systemic therapy (ST) vs. 2.6 months for patients who did not (p < 0.001). Median OS was similar for patients treated with ex20ins-specific tyrosine kinase inhibitors (TKIs) vs. other STs (18.6 vs. 15.9 months; p = 0.463). The median first-line PFS was 4.1 vs. 7.4 months for patients treated with a TKI vs. other ST (p = 0.744). For the HER2 cohort, the median OS was 9.0 months for patients who received any ST vs. 4.9 months for patients who did not (p = 0.015). The median OS was 23.0 months for patients treated with an ex20ins TKI vs. 5.6 months for patients who were not (p = 0.019). The median first-line PFS was 5.4 vs. 2.1 months for patients treated with a TKI vs. other ST (p = 0.343). (4) Conclusions: Overall survival was significantly longer among ex20ins patients who received any systemic therapy vs. those who did not. Overall survival was significantly better among HER2 ex20ins patients who received ex20ins-specific TKIs.

Beyond PACIFIC: Real-World Outcomes of Adjuvant Durvalumab According to Treatment Received and PD-L1 Expression.

Adjuvant durvalumab after chemoradiotherapy (CRT) is the standard of care for unresectable stage III non-small cell lung cancer (NSCLC). A post hoc exploratory analysis of PACIFIC revealed no OS benefit in the PD-L1 < 1% subgroup. This retrospective analysis assesses the real-world impact of durvalumab on OS according to PD-L1 tumor proportion score (TPS). Patients with stage III, unresectable NSCLC treated by CRT, with available PD-L1 TPS, from 1 March 2018 to 31 December 2020, at BC Cancer, British Columbia, Canada were included. Patients were divided into two groups, CRT + durvalumab and CRT alone. OS and PFS were analyzed in the PD-L1 ≥ 1% and <1% subgroups. A total of 134 patients were included in the CRT + durvalumab group and 117, in the CRT alone group. Median OS was 35.9 months in the CRT + durvalumab group and 27.4 months in the CRT alone group [HR 0.59 (95% CI 0.42-0.83), p = 0.003]. Durvalumab improved OS in the PD-L1 ≥ 1% [HR 0.53 (95% CI 0.34-0.81), p = 0.003, n = 175], but not in the <1% subgroup [HR 0.79 (95% CI 0.44-1.42), p = 0.4, n = 76]. This retrospective study demonstrates a statistically significant improvement in OS associated with durvalumab after CRT in PD-L1 ≥ 1%, but not PD-L1 < 1% NSCLC. Variables not accounted for may have biased the survival analysis. A prospective study would bring more insight.

Real-World Outcomes of Stage IV NSCLC with PD-L1 ≥ 50% Treated with First-Line Pembrolizumab: Uptake of Second-Line Systemic Therapy.

INTRODUCTION: Platinum-based chemotherapy was compared to single-agent pembrolizumab in advanced non-small cell lung cancer (NSCLC) with PDL1 > 50% in KEYNOTE-024. In this trial, it was found that patients who received single-agent pembrolizumab had improved progression-free survival in addition to overall survival (OS). Based on KEYNOTE-024, only 53% of patients treated originally with pembrolizumab received second-line anticancer systemic therapy with an OS of 26.3 months. Based on these results, the objective of this study was to characterize real-world NSCLC patients who received second-line therapy after single-agent pembrolizumab. METHODS: This was a retrospective cohort study considering stage IV NSCLC patients diagnosed with BC Cancer between 2018 and 2021 with PD-L1 ≥ 50% who received first-line single agent pembrolizumab. Patient demographics, cancer history, treatment administered, and survival were collected retrospectively. Descriptive statistics were produced. OS was calculated using Kaplan-Meier curves and compared using the log rank test. A multivariate model evaluated characteristics associated with the receipt of second-line therapy. RESULTS: A total of 718 patients were diagnosed with Stage IV NSCLC and received at least one cycle of pembrolizumab. The median duration of treatment was 4.4 months, and the follow-up duration was 16.0 months. There were 567 (79%) patients who had disease progression, of whom 21% received second-line systemic therapy. Within the subset of patients with disease progression, the median duration of treatment was 3.0 months. It would be found that patients who received second-line therapy had better baseline ECOG performance status, were younger at diagnosis, and had a longer duration of pembrolizumab. Within the full population, the OS from the treatment initiation date was 14.0 months. OS was 5.6 months in patients who did not receive additional therapy after progression and 22.2 months in patients who received subsequent therapy. Baseline ECOG performance status was associated with improved OS in multivariate analysis. CONCLUSION: Based on this real-world Canadian population, 21% of patients received second-line systemic therapy, despite second-line therapy being associated with prolonged survival. In this real-world population, we found that 60% fewer patients received second-line systemic therapy when compared to KEYNOTE-024. Although differences always exist when comparing a clinical and non-clinical trial population, our findings suggest undertreating stage IV NSCLC patients.

Prediction of Disease Progression to Upfront Pembrolizumab Monotherapy in Advanced Non-Small-Cell Lung Cancer with High PD-L1 Expression Using Baseline CT Disease Quantification and Smoking Pack Years.

Health Canada approved pembrolizumab in the first-line setting for advanced non-small-cell lung cancer with PD-L1 ≥ 50% and no EGFR/ALK aberration. The keynote 024 trial showed 55% of such patients progress with pembrolizumab monotherapy. We propose that the combination of baseline CT and clinical factors can help identify those patients who may progress. In 138 eligible patients from our institution, we retrospectively collected their baseline variables, including baseline CT findings (primary lung tumor size and metastatic site), smoking pack years, performance status, tumor pathology, and demographics. The treatment response was assessed via RECIST 1.1 using the baseline and first follow-up CT. Associations between the baseline variables and progressive disease (PD) were tested by logistic regression analyses. The results showed 46/138 patients had PD. The baseline CT "number of involved organs" by metastasis and smoking pack years were independently associated with PD (p < 0.05), and the ROC analysis showed a good performance of the model that integrated these variables in predicting PD (AUC: 0.79). This pilot study suggests that the combination of baseline CT disease and smoking PY can identify who may progress on pembrolizumab monotherapy and can potentially facilitate decision-making for the optimal first-line treatment in the high PD-L1 cohort.

Improved uptake and survival with systemic treatments for metastatic non-small cell lung cancer: younger versus older adults.

BACKGROUND: Over the past decade, there has been increasing availability of novel therapeutics with improved tolerability and efficacy for advanced non-small cell lung cancer (NSCLC). The study goals were: to compare the uptake of systemic therapy (ST) before and after the availability of targeted tyrosine kinase inhibitors (TKI) and immunotherapy and to examine the changes in overall survival (OS) over time between younger and older adults with advanced NSCLC. METHODS: All patients with advanced NSCLC referred to British Columbia (BC) Cancer in 2009, 2011, 2015 and 2017 were included. One-year time points were based on molecular testing implementation and funded drug availability: baseline (2009), epidermal growth factor receptor TKI (2011), anaplastic lymphoma kinase TKI (2015) and Programed Death-1 (PD-1) inhibitors (2017). Age groups were <70years and ≥70years. Baseline demographics, simplified comorbidity scores (SCS), disease characteristics, and ST details were collected retrospectively. Variables were compared using X2, Fisher's exact tests and logistic-regression analysis. OS was calculated using the Kaplan-Meier method and compared using the log-rank test. RESULTS: 3325 patients were identified. Baseline characteristics were compared between ages < 70 years and ≥ 70 years for each time cohort with significant differences noted in baseline Eastern Cooperative Oncology Group (ECOG) performance status and SCS. The rate of ST delivery trended upwards over time with age <70 years: 2009 44%, 2011 53%, 2015 50% and 2017 52% and age ≥70 years: 22%, 25%, 28% and 29% respectively. Predictors for decreased use of ST for age <70 years: ECOG ≥2, SCS ≥9, year 2011, and smoking history; and age ≥70 years: ECOG ≥2, years 2011 and 2015, and smoking history. The median OS of patients who received ST improved from 2009 to 2017: age <70 years 9.1 m vs. 15.5 m and age ≥70 years 11.4 m vs. 15.0 m. CONCLUSIONS: There was an increased uptake of ST for both age groups with the introduction of novel therapeutics. Although a smaller proportion of older adults received ST, those who received treatment had comparable OS to their young counterpart. The benefit of ST in both age groups was seen across the different types of treatments. With careful assessment and selection of appropriate candidates, older adults with advanced NSCLC appear to benefit from ST.

The perceptions and adoption of environmentally sustainable practices among anesthesiologists-a qualitative study.

PURPOSE: Previous surveys of anesthesiologists showed that despite a strong interest in implementing environmentally sustainable anesthetic practices, less than a third do so. Qualitative understanding of the capability, opportunity, and motivational factors that influence "green" behavior will inform the design of effective interventions to promote environmentally sustainable practices in the operating room (OR). METHODS: We conducted 23 semistructured interviews with anesthesiologists, with data saturation achieved. Applying the Behavior Change Wheel, interview questions addressed "capability," "opportunity," and "motivation" determinants of behavior. RESULTS: Preference for sevoflurane and syringe reuse were most commonly cited as existing environmentally sustainable anesthetic practices. Several participants reported lack of knowledge and feedback as impediments to sustainable anesthetic practices. Reported physical barriers included inadequate recycling facilities and abundance of supplies. Interviewees also discussed the importance of habitual behavior in improving skill sets and reducing cognitive load required to perform environmentally sustainable practices. General awareness of environmental issues and aggregation of marginal gains were reasons for environmentally sustainable measures in the OR. Organizational practice and culture played a significant role in the propagation of sustainable anesthetic practices, with senior staff often carrying a greater influence. While the majority preferred a top-down approach to effect change, others favored the use of incentives. CONCLUSION: This study provides insight into the factors that influence the adoption of environmentally sustainable practices in the OR. Measures to promote these practices include education and training, feedback on efforts, engagement of senior anesthetists as role models and for change management, environmental restructuring, and policy designs that balance a top-down vs bottom-up approach to influencing change.

RéSUMé: OBJECTIF: Des enquêtes antérieures auprès d'anesthésiologistes ont montré que, malgré un vif intérêt pour la mise en œuvre de pratiques anesthésiques durables sur le plan environnemental, moins d'un tiers les mettent en pratique. La compréhension qualitative de la capacité, des possibilités et des facteurs de motivation qui influencent les comportements « verts ¼ éclairera la conception d'interventions efficaces pour promouvoir des pratiques durables sur le plan environnemental en salle d'opération. MéTHODE: Nous avons mené 23 entretiens semi-structurés avec des anesthésiologistes, avec une saturation des données atteinte. En appliquant la roue du changement de comportement, les questions d'entrevue portaient sur les déterminants du comportement liés à la « capacité ¼, à l'« occasion ¼ et à la « motivation ¼. RéSULTATS: La préférence pour le sévoflurane et la réutilisation des seringues ont été le plus souvent citées comme des pratiques anesthésiques durables. Plusieurs participants ont signalé que le manque de connaissances et de rétroaction constituait un obstacle à des pratiques anesthésiques durables. Parmi les obstacles physiques signalés, mentionnons l'insuffisance des installations de recyclage et l'abondance des fournitures. Les personnes interrogées ont également discuté de l'importance du comportement habituel pour améliorer les compétences et réduire la charge cognitive requise pour mettre en œuvre des pratiques durables. La prise de conscience générale des questions environnementales et l'agrégation des gains marginaux étaient les raisons citées pour lesquelles des mesures écologiquement viables ont été prises en salle d'opération. La pratique organisationnelle et la culture ont joué un rôle important dans la diffusion de pratiques anesthésiques durables, les cadres supérieurs ayant souvent une plus grande influence. Alors que la majorité préférerait une approche descendante pour apporter des changements, d'autres étaient en faveur de l'utilisation d'incitatifs. CONCLUSION: Cette étude donne un aperçu des facteurs qui influencent l'adoption de pratiques durables sur le plan environnemental en salle d'opération. Les mesures visant à promouvoir ces pratiques comprennent l'éducation et la formation, la rétroaction sur les efforts, l'engagement des anesthésistes plus établis ou senior en tant que modèles et gestionnaires du changement, la restructuration environnementale et la conception de politiques qui équilibrent une approche descendante vs une approche ascendante pour influencer le changement.

Predicting the Survival of Patients With Cancer From Their Initial Oncology Consultation Document Using Natural Language Processing.

Importance: Predicting short- and long-term survival of patients with cancer may improve their care. Prior predictive models either use data with limited availability or predict the outcome of only 1 type of cancer. Objective: To investigate whether natural language processing can predict survival of patients with general cancer from a patient's initial oncologist consultation document. Design, Setting, and Participants: This retrospective prognostic study used data from 47 625 of 59 800 patients who started cancer care at any of the 6 BC Cancer sites located in the province of British Columbia between April 1, 2011, and December 31, 2016. Mortality data were updated until April 6, 2022, and data were analyzed from update until September 30, 2022. All patients with a medical or radiation oncologist consultation document generated within 180 days of diagnosis were included; patients seen for multiple cancers were excluded. Exposures: Initial oncologist consultation documents were analyzed using traditional and neural language models. Main Outcomes and Measures: The primary outcome was the performance of the predictive models, including balanced accuracy and receiver operating characteristics area under the curve (AUC). The secondary outcome was investigating what words the models used. Results: Of the 47 625 patients in the sample, 25 428 (53.4%) were female and 22 197 (46.6%) were male, with a mean (SD) age of 64.9 (13.7) years. A total of 41 447 patients (87.0%) survived 6 months, 31 143 (65.4%) survived 36 months, and 27 880 (58.5%) survived 60 months, calculated from their initial oncologist consultation. The best models achieved a balanced accuracy of 0.856 (AUC, 0.928) for predicting 6-month survival, 0.842 (AUC, 0.918) for 36-month survival, and 0.837 (AUC, 0.918) for 60-month survival, on a holdout test set. Differences in what words were important for predicting 6- vs 60-month survival were found. Conclusions and Relevance: These findings suggest that models performed comparably with or better than previous models predicting cancer survival and that they may be able to predict survival using readily available data without focusing on 1 cancer type.

Economic impact of using risk models for eligibility selection to the International lung screening Trial.

OBJECTIVES: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013). MATERIALS AND METHODS: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials. The primary outcomes were costs in 2020 International Dollars ($), quality-adjusted life-years (QALY) and incremental net benefit (INB, in $ per QALY). Secondary outcomes were selection characteristics and cancer detection rates (CDR). RESULTS: Compared with the USPSTF-2013 criteria, the PLCOm2012 risk model resulted in $355 of cost savings per 0.2 QALYs gained (INB=$4294 at a willingness-to-pay threshold of $20 000/QALY (95 %CI: $4205-$4383). Using the risk model was more cost-effective in females at both a 1.5 % and 1.7 % 6-year risk threshold (INB=$6616 and $6112, respectively), compared with males ($5221 and $695). The PLCOm2012 model selected more females, more individuals with fewer years of formal education, and more people with other respiratory illnesses in the ILST. The CDR with the risk model was higher in females compared with the USPSTF-2013 criteria (Risk Ratio = 7.67, 95 % CI: 1.87-31.38). CONCLUSION: The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening.

Use, response and outcomes of second-line chemotherapy in patients with advanced biliary tract cancers.

INTRODUCTION: First-line chemotherapy for advanced biliary tract cancers has been established as gemcitabine and cisplatin; however, there is currently no recognized standard second-line chemotherapy. The purpose of this study is to review and evaluate the outcomes of second-line chemotherapy for advanced biliary tract cancers. METHODS: Patients who received chemotherapy for unresectable or metastatic biliary tract cancers at BC Cancer between August 2009 and December 2015 were retrospectively studied to identify second-line chemotherapy treatments used and to determine overall survival, time-to-treatment discontinuation and characteristics predicting for improved overall survival. RESULTS: Of 325 patients who received first-line chemotherapy for advanced biliary tract cancer, 90 (30%) received second-line chemotherapy. Median overall survival for patients who received only first-line chemotherapy was 9.5 months versus 17.3 months for patients who received second-line chemotherapy. Median time-to-treatment discontinuation for second-line chemotherapy was 2.0 months. Common drugs used in second-line chemotherapy treatments included capecitabine (30%), 5-fluorouracil and irinotecan (17%) and 5-fluorouracil monotherapy (15%). There was no difference in overall survival for patients who received single-agent second-line chemotherapy compared to doublet second-line chemotherapy. CONCLUSIONS: Patients who are fit enough to receive second-line chemotherapy may benefit in terms of overall survival and should be offered treatment with single-agent therapy. Capecitabine was the most common second-line chemotherapy treatment. The improved median overall survival for patients who received second-line chemotherapy may be impacted by independent patient-specific factors which are unknown at this time.

Real World Patient Eligibility for Second Line Lurbinectedin Based Treatment in Small Cell Lung Cancer: Understanding Epidemiology and Estimating Health Care Utilization.

BACKGROUND: In the ATLANTIS study, second-line lurbinectedin/doxorubicin did not improve overall survival (OS), however patients with a chemotherapy-free interval (CTFI) of ≥180 days had an improved progression free survival (PFS). The objective of this retrospective study was to identify the proportion of real-world small cell lung cancer (SCLC) patients who are suitable for lurbinectedin-based therapy based on these criteria. METHODS: A retrospective study of all SCLC referred to BC Cancer between 2012 and 2017 was conducted. Patient demographics, staging, treatment, and survival data were collected retrospectively. Baseline characteristics were compared using descriptive statistics. OS was calculated using Kaplan-Meier curves. Statistically significant p-value was <0.05. RESULTS: A total of 1048 patients were identified. Baseline characteristics: median age 68 years, 47% male, 61% current smoking status, 68% extensive disease. Best supportive care was received by 22%. First-line systemic therapy was platinum doublet for 71% of the population. Second-line systemic therapy was delivered to 22%. Of the 219 patients who received second-line systemic therapy after platinum doublet, 183 patients had a CTFI of ≥90 days and 107 patients had a CTFI of ≥180 days. Patients originally treated as limited stage disease, received platinum doublet as second line, received thoracic radiation (RT) or prophylactic cranial irradiation (PCI) were more likely to have a CTFI of ≥90 and ≥180 days. CONCLUSION: In our real-world SCLC population, only 21% of the SCLC population received second-line therapy after platinum doublet with 17% achieving CTFI of ≥90 days and 10% CTFI of ≥180 days. Based on this retrospective review, only a small fraction of platinum-treated patients would be preferentially offered lurbinectedin in the second-line setting.

International recommendations for plasma Epstein-Barr virus DNA measurement in nasopharyngeal carcinoma in resource-constrained settings: lessons from the COVID-19 pandemic.

The effects of the COVID-19 pandemic continue to constrain health-care staff and resources worldwide, despite the availability of effective vaccines. Aerosol-generating procedures such as endoscopy, a common investigation tool for nasopharyngeal carcinoma, are recognised as a likely cause of SARS-CoV-2 spread in hospitals. Plasma Epstein-Barr virus (EBV) DNA is considered the most accurate biomarker for the routine management of nasopharyngeal carcinoma. A consensus statement on whether plasma EBV DNA can minimise the need for or replace aerosol-generating procedures, imaging methods, and face-to-face consultations in managing nasopharyngeal carcinoma is urgently needed amid the current pandemic and potentially for future highly contagious airborne diseases or natural disasters. We completed a modified Delphi consensus process of three rounds with 33 international experts in otorhinolaryngology or head and neck surgery, radiation oncology, medical oncology, and clinical oncology with vast experience in managing nasopharyngeal carcinoma, representing 51 international professional societies and national clinical trial groups. These consensus recommendations aim to enhance consistency in clinical practice, reduce ambiguity in delivering care, and offer advice for clinicians worldwide who work in endemic and non-endemic regions of nasopharyngeal carcinoma, in the context of COVID-19 and other airborne pandemics, and in future unexpected settings of severe resource constraints and insufficiency of personal protective equipment.

Alternate Pembrolizumab Dosing Interval in Advanced NSCLC with PD-L1 TPS ≥ 50%: 3 Weekly Compared to 6 Weekly Dosing.

BACKGROUND: A fixed dose of 200 mg of pembrolizumab every 3 weeks (Q3W) is the standard of care for patients with stage IV non-small cell lung cancer (NSCLC) and PDL1 ≥50%. In April 2020, based on pharmacokinetic modeling without formal comparative studies, the FDA approved 400 mg every 6 weeks (Q6W). Pharmacokinetic studies also suggested comparable target engagement with weight-based and flat dosing for the respective schedules. The objective of this study was to determine if overall survival (OS) differs based on the Q3W vs. Q6W dosing schedule of pembrolizumab. METHODS: BC Cancer patients with stage IV NSCLC and PDL1 ≥50% treated with pembrolizumab were retrospectively reviewed. Patients were treated with weight-based dosing, per institution standard, of pembrolizumab 2 mg/kg Q3W or 4 mg/kg Q6W. Patient demographics, treatment and outcome were recorded. Patients were assigned to Q3W or Q6W according to the schedule that was used for the majority of treatment (greater than 50%). RESULTS: 718 patients with NSCLC and PDL1 ≥50% received first-line pembrolizumab between 2017 and2021, Q3W/Q6W dosing 677/41 patients. Baseline characteristics with respect to age, sex, smoking status, histology and performance status (PS) were similar between groups. In the multivariate model, including age, sex, PS and dosing schedule, the hazard ratio for death (HR) for OS Q3W vs. Q6W was 0.759 (p = 0.230). A 2:1 case-matched analysis for OS was performed, controlling for sex, age ± 5 years, PS and duration on pembrolizumab ± 2 months for Q3W vs. Q6W (n = 113) with a HR 0.834 (p = 0.500). CONCLUSIONS: There was no OS difference demonstrated with pembrolizumab dosing Q3W compared to Q6W in a multivariate analysis that included age, sex and PS. A case-matched analysis that controlled for these variables and for duration of treatment confirmed these findings. This study supports the use of Q6W pembrolizumab dosing, allowing for less frequent interactions with the medical system.

A perspective on life-cycle health technology assessment and real-world evidence for precision oncology in Canada.

Health technology assessment (HTA) can be used to make healthcare systems more equitable and efficient. Advances in precision oncology are challenging conventional thinking about HTA. Precision oncology advances are rapid, involve small patient groups, and are frequently evaluated without a randomized comparison group. In light of these challenges, mechanisms to manage precision oncology uncertainties are critical. We propose a life-cycle HTA framework and outline supporting criteria to manage uncertainties based on real world data collected from learning healthcare systems. If appropriately designed, we argue that life-cycle HTA is the driver of real world evidence generation and furthers our understanding of comparative effectiveness and value. We conclude that life-cycle HTA deliberation processes must be embedded into healthcare systems for an agile response to the constantly changing landscape of precision oncology innovation. We encourage further research outlining the core requirements, infrastructure, and checklists needed to achieve the goal of learning healthcare supporting life-cycle HTA.