Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data.

BACKGROUND: Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta's biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses. Previous work on extracting relevant information from free text, unstructured data employed Natural Language Processing (NLP), Machine Learning (ML), rule-based Information Extraction (IE) methods, or a hybrid combination between them. METHODS: In our study, text analysis was performed on Alberta Precision Laboratories data which consisted of 95,854 entries from the Southern Alberta Dataset (SAD) and 6944 entries from the Northern Alberta Dataset (NAD). The data covers all of Alberta and is completely population-based. Our proposed framework is built around rule-based IE methods. It incorporates topics such as Syntax and Lexical analyses to achieve deterministic extraction of data from biomarker laboratory data (i.e., Epidermal Growth Factor Receptor (EGFR) test results). Lexical analysis compromises of data cleaning and pre-processing, Rich Text Format text conversion into readable plain text format, and normalization and tokenization of text. The framework then passes the text into the Syntax analysis stage which includes the rule-based method of extracting relevant data. Rule-based patterns of the test result are identified, and a Context Free Grammar then generates the rules of information extraction. Finally, the results are linked with the Alberta Cancer Registry to support real-world cancer research studies. RESULTS: Of the original 5512 entries in the SAD dataset and 5017 entries in the NAD dataset which were filtered for EGFR, the framework yielded 5129 and 3388 extracted EGFR test results from the SAD and NAD datasets, respectively. An accuracy of 97.5% was achieved on a random sample of 362 tests. CONCLUSIONS: We presented a text analysis framework to extract specific information from unstructured clinical data. Our proposed framework has shown that it can successfully extract relevant information from EGFR test results.

The Association between Red Meat Consumption and Advanced Colorectal Adenomas in a Population Undergoing a Screening-Related Colonoscopy in Alberta, Canada.

The association between red meat consumption and colorectal cancer has been rigorously examined. However, a more comprehensive understanding of how the intake of unprocessed red meat contributes to the development of early precancerous colorectal lesions, such as advanced colorectal adenomas (ACRAs), requires further investigation. We examined the associations between different types of red meat intake and ACRAs in a sample population of 1083 individuals aged ≥ 50 years undergoing an initial screening colonoscopy in Calgary, Alberta, Canada. Associations between grams per day of total, processed, and unprocessed red meat from diet history questionnaires and ACRAs were evaluated with multivariable logistic regression models. We also applied cubic spline models fitted with three knots (10th, 50th, and 90th percentiles) to identify potential nonlinear associations. We did not observe a meaningful association between unprocessed red meat intake and the presence of ACRAs. In contrast, for every 10 g/d increase in total and processed meat intake, we observed an increase in the odds of ACRAs at the screening colonoscopy (adjusted odds ratio (OR) = 1.05, 95% [CI = 1.01-1.09], p = 0.04) and (adjusted OR = 1.11, 95% [CI = 1.02-1.20], p = 0.02), respectively. This study highlights the importance of differentiating between types of red meat consumption in the context of dietary risks associated with ACRAs.

Real-World Treatment Patterns, Clinical Outcomes, and Healthcare Resource Utilization in Early-Stage Non-Small-Cell Lung Cancer.

The prognosis of early non-small-cell lung cancer (eNSCLC) remains poor. An understanding of current therapies and outcomes can provide insights into how novel therapies can be integrated into clinics. We conducted a large, retrospective, population-based cohort study of patients with de novo eNSCLC (stages IB, IIA, IIB, and IIIA) diagnosed in Alberta, Canada, between 2010 and 2019. The primary objectives were to describe treatment patterns and survival outcomes among patients with eNSCLC. A total of 5126 patients with eNSCLC were included. A total of 45.3% of patients were referred to a medical oncologist, ranging from 23.7% in stage IB to 58.3% in IIIA. A total of 23.6% of patients initiated systemic therapy (ST), ranging from 3.5% in stage IB to 38.5% in IIIA. For stage IIB and IIIA individuals who received surgery, adjuvant ST was associated with a decreased likelihood of death (hazard ratios (HR) of 0.77 (95% CI: 0.56-1.07) and 0.69 (95% CI: 0.54-0.89), respectively). In a Canadian real-world setting, stage IIB and IIIA patients who received adjuvant ST tended to have better survival than patients who did not, but future studies that provide adjustment of additional confounders are warranted. Examining referral pathways that account for disparities based on age, sex, and comorbidities in the real world would also provide further insights.

The association between neighborhood-level income and cancer stage at diagnosis and survival in Alberta.

BACKGROUND: Socioeconomic status (SES) is associated with a range of health outcomes, including cancer diagnosis and survival. However, the evidence for this association is inconsistent between countries with and without single-payer health care systems. In this study, the relationships between neighborhood-level income, cancer stage at diagnosis, and cancer-specific mortality in Alberta, Canada, were evaluated. METHODS: The Alberta Cancer Registry was used to identify all primary cancer diagnoses between 2010 and 2020. Average neighborhood income was determined by linking the Canadian census to postal codes and was categorized into quintiles on the basis of income distribution in Alberta. Multivariable multinomial logistic regression was used to model the association between income quintile and stage at diagnosis, and the Fine-Gray proportional subdistribution hazards model was used to estimate the association between SES and cancer-specific mortality. RESULTS: Out of the 143,818 patients with cancer included in the study, those in lower income quintiles were significantly more likely to be diagnosed at stage III (odds ratio [OR], 1.07; 95% CI [confidence interval], 1.06-1.09) or IV (OR, 1.12; 95% CI, 1.11-1.14) after adjusting for age and sex. Lower income quintiles also had significantly worse cancer-specific survival for breast, colorectal, liver, lung, non-Hodgkin lymphoma, oral cavity, pancreas, and prostate cancers. CONCLUSIONS: Disparities were observed in cancer outcomes across neighborhood-level income groups in Alberta, which demonstrates that health inequities by SES exist in countries with single-payer health care systems. Further research is needed to better understand the underlying causes and to develop strategies to mitigate these disparities.

Association between treatment and improvements in overall survival of patients with advanced/metastatic non-small cell lung cancer since 2011: A study in the United States, Canada, and Germany using retrospective real-world databases.

BACKGROUND: This study aimed to describe treatment patterns and overall survival (OS) in patients with advanced non-small cell lung cancer (aNSCLC) in three countries between 2011 and 2020. METHODS: Three databases (US, Canada, Germany) were used to identify incident aNSCLC patients. OS was assessed from the date of incident aNSCLC diagnosis and, for patients who received at least a first line of therapy (1LOT), from the date of 1LOT initiation. In multivariable analyses, we analyzed the influence of index year and type of prescribed treatment on OS. FINDINGS: We included 51,318 patients with an incident aNSCLC diagnosis. The percentage of patients treated with a 1LOT differed substantially between countries, whereas the number of patients receiving immunotherapies/targeted treatments increased over time in all three countries. Median OS from the date of incident diagnosis was 9.9 months in the United States vs. 4.1 months in Canada. When measured from the start of 1LOT, patients had a median OS of 10.7 months in the United States, 10.9 months in Canada, and 10.9 months in Germany. OS from the start of 1LOT improved in all three countries from 2011 to 2020 by approximately 3 to 4 months. CONCLUSIONS: Observed continuous improvement in OS among patients receiving at least a 1LOT from 2011 to 2020 was likely driven by improved care and changes in the treatment landscape. The difference in the proportion of patients receiving a 1LOT in the observed countries requires further investigation.

Exploring the Future of Cancer Impact in Alberta: Projections and Trends 2020-2040.

The impact of cancer in Alberta is expected to grow considerably, largely driven by population growth and aging. The Future of Cancer Impact (FOCI) initiative offers an overview of the present state of cancer care in Alberta and highlights potential opportunities for research and innovation across the continuum. In this paper, we present a series of detailed projections and analyses regarding cancer epidemiological estimates in Alberta, Canada. Data on cancer incidence and mortality in Alberta (1998-2018) and limited-duration cancer prevalence in Alberta (2000-2019) were collected from the Alberta Cancer Registry. We used the Canproj package in the R software to project these epidemiological estimates up to the year 2040. To estimate the direct management costs, we ran a series of microsimulations using the OncoSim All Cancers Model. Our findings indicate that from 2020, the total number of annual new cancer cases and cancer-related deaths are projected to increase by 56% and 49% by 2040, respectively. From 2019, the five-year prevalence of all cancers in Alberta is projected to increase by 86% by 2040. In line with these trends, the overall direct cost of cancer management is estimated to increase by 53% in 2040. These estimates and projections are integral to future strategic planning and investment.

Real-world impact of patient-reported outcome measurement on overall survival, healthcare use and treatment discontinuation in cancer patients.

Aim: The purpose of this retrospective, population-based, observational cohort analysis was to assess whether routine patient-reported outcomes (PRO) monitoring alone has an impact on real-world overall survival (OS) and hospitalizations among individuals diagnosed with lung, breast or colorectal cancer. The importance of follow-up care in post-PRO data collection was also discussed. Patients & methods: Administrative databases covering 17 cancer centers from Alberta, Canada were queried and individuals ≥18 years old and diagnosed with lung, breast or colorectal cancer from 1 January 2016 to 31 December 2019 were included and followed until 31 December 2020. Patients were stratified by whether they received routine PRO monitoring initiated within 120 days of diagnosis and matched 1:1 with use of propensity scores based on baseline characteristics. OS was assessed from the index date to death, and the respective Kaplan-Meier curves were estimated along with hazard ratios from Cox Proportional Hazard Models. Linear and logistic regression models were used to estimate mean differences and odds ratios (OR) respectively for healthcare resource utilization events including cancer physician visits, emergency department visits and outpatient ambulatory care encounters. Results: 4800 patients were included in each matched cohort. There was no statistically significant difference between PRO monitoring and non-monitoring cohorts in OS (HR = 1.01; 95% CI: 0.93-1.09; p = 0.836) and treatment discontinuation (OR = 0.98; 95% CI: 0.85-1.12; p = 0.75). Median OS was 51.5 months for unmonitored cohort (95% CI: 47.5-NA) versus 50.6 months for monitored cohort (95% CI: 47.6-55.7). Compared with PRO-monitored patients, unmonitored patients were associated with lower hospitalization risks (OR = 1.12; 95% CI: 1.03-1.22; p = 0.01). However, PRO-monitored patients experienced significantly fewer physician visits in comparison to unmonitored patients (MD = -1.036; 95% CI: -1.288 to -0.784, p < 0.001). Conclusion: Our results show that capturing patient-reported symptoms alone reduced the number of physician visits but neither reduced hospitalizations nor improved OS in this real-world cancer population. To drive more meaningful clinical impact, PRO monitoring programs must be met with rigorous follow-up response to the identified symptoms.

Impact of the COVID-19 pandemic on cancer diagnoses, stage and survival in Alberta.

BACKGROUND: The COVID-19 pandemic is suspected to have affected cancer care and outcomes among patients in Canada. In this study, we evaluated the impact of the state of emergency period during the COVID-19 pandemic (Mar. 17 to June 15, 2020) on cancer diagnoses, stage at diagnosis and 1-year survival in Alberta. METHODS: We included new diagnoses of the 10 most prevalent cancer types from Jan. 1, 2018, to Dec. 31, 2020. We followed patients up to Dec. 31, 2021. We used interrupted time series analysis to examine the impact of the first COVID-19-related state of emergency in Alberta on the number of cancer diagnoses. We used multivariable Cox regression to compare 1-year survival of the patients who received a diagnosis during 2020 after the state of emergency with those who received a diagnosis during 2018 and 2019. We also performed stage-specific analyses. RESULTS: We observed significant reductions in diagnoses of breast cancer (incidence rate ratio [IRR] 0.67, 95% confidence interval [CI] 0.59-0.76), prostate cancer (IRR 0.64, 95% CI 0.56-0.73) and colorectal cancer (IRR 0.64, 95% CI 0.56- 0.74) and melanoma (IRR 0.57, 95% CI 0.47-0.69) during the state of emergency period compared with the period before it. These decreases largely occurred among early-stage rather than late-stage diagnoses. Patients who received a diagnosis of colorectal cancer, non-Hodgkin lymphoma and uterine cancer in 2020 had lower 1-year survival than those diagnosed in 2018; no other cancer sites had lower survival. INTERPRETATION: The results from our analyses suggest that health care disruptions during the COVID-19 pandemic in Alberta considerably affected cancer outcomes. Given that the largest impact was observed among early-stage cancers and those with organized screening programs, additional system capacity may be needed to mitigate future impact.

Time spent in the sun and the risk of developing non-Hodgkin lymphoma: a Canadian cohort study.

PURPOSE: The objective was to explore the relationship of sun behavior patterns with the risk of developing non-Hodgkin lymphoma (NHL). METHODS: Sun behavior information from Alberta's Tomorrow Project, CARTaGENE, and Ontario Health Study were utilized. The relationship between time in the sun during summer months and risk of NHL was assessed using Cox proportional hazard models with age as the time scale and adjustment for confounders. Cohorts were analyzed separately and hazard ratios (HR) pooled with random effects meta-analysis. Joint effects of time in the sun and use of sun protection were examined. Patterns of exposure were explored via combinations of weekday and weekend time in the sun. RESULTS: During an average follow-up of 7.6 years, 205 NHL cases occurred among study participants (n = 79,803). Compared to < 30 min daily in the sun, we observed HRs of 0.84 (95% CI 0.55-1.28) for 30-59 min, 0.63 (95% CI 0.40-0.98) for 1-2 h, and 0.91 (95% CI 0.61-1.36) for > 2 h. There was suggestive evidence that > 2 h was protective against NHL with use of sun protection, but not without it. Compared to < 30 min daily, moderate exposure (30 min to 2 h on weekdays or weekend) was associated with a lower risk of NHL (HR 0.63, 95% CI 0.43-0.92), while intermittent (< 30 min on weekdays and > 2 h on weekends) and chronic (> 2 h daily) were not. CONCLUSION: This study provides evidence of a protective effect of moderate time spent in the sun on NHL risk.

Understanding Real-World Treatment Patterns and Clinical Outcomes among Metastatic Melanoma Patients in Alberta, Canada.

Immunotherapy and targeted therapies have been shown to considerably improve long-term survival outcomes in metastatic melanoma patients. Real-world evidence on the uptake of novel therapies and outcomes for this patient population in Canada are limited. We conducted a population-based retrospective cohort study of all metastatic melanoma patients diagnosed in Alberta, Canada (2015-2018) using electronic medical records and administrative data. Information on BRAF testing for patients diagnosed in 2017 or 2018 was obtained through chart abstraction. In total, 434 metastatic melanoma patients were included, of which 110 (25.3%) were de novo metastatic cases. The median age at diagnosis was 66 years (IQR: 57-76) and 70.0% were men. BRAF testing was completed for the majority of patients (88.7%). Among all patients, 60.4%, 19.1%, and 6.0% initiated first-line, second-line, and third-line systemic therapy. The most common therapies were anti-PD-1 and targeted therapies. The two-year survival probability from first-line therapy, second-line therapy, and third-line therapy was 0.50 (95% CI: 0.44-0.57), 0.26 (95% CI: 0.17-0.40), and 0.14 (95% CI: 0.40-0.46), respectively. In the first-line setting, survival was highest for patients that received ipilimumab or ipilimumab plus nivolumab, while targeted therapy had the highest survival in the second-line setting. This study indicates that novel therapies improve survival in the real world but a considerable proportion of patients do not receive treatment with systemic therapy.

Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors.

BACKGROUND: Risk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS). PATIENTS AND METHODS: A total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines. RESULTS: High white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65. CONCLUSIONS: Liver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

The Association between Early-Onset Diagnosis and Clinical Outcomes in Triple-Negative Breast Cancer: A Systematic Review and Meta-Analysis.

Early-onset diagnosis, defined by age <40 years, has historically been associated with inferior outcomes in breast cancer. Recent evidence suggests that this association is modified by molecular subtype. We performed a systematic review and meta-analysis of the literature to synthesize evidence on the association between early-onset diagnosis and clinical outcomes in triple-negative breast cancer (TNBC). Studies comparing the risk of clinical outcomes in non-metastatic TNBC between early-onset patients and later-onset patients (≥40 years) were queried in Medline and EMBASE from inception to February 2023. Separate meta-analyses were performed for breast cancer specific survival (BCSS), overall survival (OS), and disease-free survival (DFS), locoregional recurrence-free survival (LRRFS), distant recurrence-free survival (DRFS), and pathological complete response (pCR). In total, 7581 unique records were identified, and 36 studies satisfied inclusion criteria. The pooled risk of any recurrence was significantly greater in early-onset patients compared to later-onset patients. Better BCSS and OS were observed in early-onset patients relative to later-onset patients aged >60 years. The pooled odds of achieving pCR were significantly higher in early-onset patients. Future studies should evaluate the role of locoregional management of TNBC and the implementation of novel therapies such as PARP inhibitors in real-world settings, and whether they improve outcomes.

Lung Immune Therapy Evaluation (LITE) Risk, a Novel Prognostic Model for Patients With Advanced Non-Small Cell Lung Cancer Treated With Immune Checkpoint Blockade.

INTRODUCTION/BACKGROUND: Immune checkpoint inhibitors (ICI) have revolutionized non-small cell lung cancer (NSCLC). We aimed to identify baseline characteristics, that are prognostic factors for overall survival (OS) in patients with NSCLC treated with ICI monotherapy, in order to derive the Lung Immune Therapy Evaluation (LITE) risk, a prognostic model. MATERIALS AND METHODS: Multi-center observational cohort study of patients with advanced NSCLC that received ≥1 dose of ICI monotherapy. The training set (n=342) consisted of patients with NSCLC who received first line ICI. The test set (n=153) used for external validation was a discrete cohort of patients who received second line ICI. 20 candidate prognostic factors were examined. Penalized Cox regression was used for variable selection. Multiple imputation was used to address missingness. RESULTS: Three baseline characteristics populated the final model: ECOG (0, 1 or ≥2), lactate dehydrogenase>upper limit of normal, and derived neutrophil to lymphocyte ratio ≥3. Patients were parsed into 3 risk groups; favorable (n=146, risk score 0-1), intermediate (n=101, risk score 2) and poor (n=95, risk score ≥3). The c-statistic of the training cohort was 0.702 and 0.694 after bootstrapping. The test cohort c-statistic was 0.664. The median OS for favorable, intermediate and poor LITE risk were; 28.3 months, 9.1 months and 2.1 months respectively. Improving LITE risk group was associated with improved OS, intermediate vs favorable HR 2.08 (95%CI 1.46-2.97, P < .001); poor vs favorable HR 5.21 (95%CI 3.69-7.34, P < .001). CONCLUSION: A simple prognostic model, utilizing accessible clinical data, can discriminate survival outcomes in patients with advanced NSCLC.

Selection Bias in Real-World Data Studies Used to Support Health Technology Assessments: A Case Study in Metastatic Cancer.

Real-world evidence has been increasingly used to support evaluations of emerging therapies. These investigations are often conducted in settings that may not be representative of the underlying population. The purpose of this investigation was to empirically quantify the magnitude of this selection bias. Individuals diagnosed with solid metastatic cancer in Alberta, Canada, between 2010-2019 were identified using the provincial cancer registry for 13 common metastatic sites. Two outcomes used to support oncology reimbursement decisions were examined: the proportion of individuals who initiated systemic therapy and median overall survival (OS). These outcomes were assessed in the entire population and in a subset of individuals who were referred to a medical oncologist. Among the 23,152 individuals in the entire population, 40.8% (95% CI: 40.2-41.4) initiated systemic therapy, and the median OS from diagnosis was 5.4 months (95% CI: 5.3-5.6). Among those who were referred to a medical oncologist (n = 13,372; 57.8%), 67.4% (95% CI: 66.6-68.2) initiated systemic therapy, and the median OS from diagnosis was 11.2 months (95% CI: 10.9-11.5). The magnitude of bias varied by cancer site where lower referral rates were associated with greater bias. Non-referral is an important source of selection bias in real-world investigations. Studies that rely on limited-catchment real-world data should be interpreted with caution, particularly in metastatic cancer settings.

Understanding Characteristics, Treatment Patterns, and Clinical Outcomes for Individuals with Advanced or Recurrent Endometrial Cancer in Alberta, Canada: A Retrospective, Population-Based Cohort Study.

Endometrial cancer (EC) incidence has increased in recent decades. However, population-based outcomes data are limited. In this retrospective cohort study, we examined characteristics, treatment patterns, and clinical outcomes, including time to next treatment (TNNT) and overall survival (OS), among advanced/recurrent (A/R) EC patients between 2010 and 2018 in Alberta, Canada. Kaplan-Meier statistics evaluated TTNT and OS, stratified by patient (A/R) and treatment. A total of 1053 patients were included: 620 (58.9%) advanced and 433 (41.1%) recurrent. A total of 713 (67.7%) patients received first-line therapy: 466 (75.2%) advanced and 247 (57.0%) recurrent. Platinum-based chemotherapy (PBCT) was the most common first-line regimen (overall: 78.6%; advanced: 96.1%; recurrent: 45.3%). The median TTNT and OS from first-line therapy were 19.9 months (95% confidence interval [CI]: 17.5-23.5) and 35.9 months (95% CI: 31.5-53.5), respectively. Following first-line PBCT, the median OS from second-line chemotherapy (N = 187) was 10.4 months (95% CI: 8.9-13.3) and higher for those rechallenged with PBCT (N = 72; 38.5%) versus no rechallenge (N = 115; 61.5%) (13.3 months [95% CI: 11.2-20.9] vs. 6.4 months [95% CI: 4.6-10.4; p < 0.001]). The findings highlight poor outcomes in A/R EC, particularly following first-line therapy, and that additional tolerable therapeutic options are needed to improve patient outcomes.

Patient-Reported Symptom Burden and Supportive Care Needs of Patients With Stage II-III Colorectal Cancer During and After Adjuvant Systemic Treatment: A Real-World Evidence Study.

PURPOSE: Patients with colorectal cancer (CRC) experience a range of physical and psychologic symptoms, and supportive care needs throughout the illness trajectory. We used patient-reported outcomes and administrative health data to describe symptom burden and supportive care needs during and after adjuvant treatment and determine factors associated with changes to symptom burden. METHODS: A retrospective population-based cohort study of patients who were newly diagnosed with stage II-III CRC in Alberta, Canada, between January 1, 2016, and January 31, 2019. Adults age 18 years or older who completed a patient-reported outcomes survey (Edmonton Symptom Assessment System) and supportive care needs (Canadian Problem Checklist) within 3 months after starting adjuvant treatment (during treatment) and > 7 months after starting treatment (after treatment) were included. Changes to symptom severity were stratified as stable, improved, or deteriorated. Multivariable logistic regression was used to evaluate factors associated with these changes. RESULTS: We included 303 patients (median age 60 years, 62% male, 84.5% stage III, 51.2% rectal v colon). Prevalent symptoms included tiredness (80.5%), pain (50.8%), and poor well-being (50%) during treatment, and tiredness (71.3%), pain (44.2%), and poor well-being (62.1%) after treatment. The results were heterogeneous with respect to improvements, stability, or deterioration. Pain worsened for 25% of the cohort, tiredness for 28%, and depression, anxiety, and well-being for 21%, 22%, and 31%, respectively. Deterioration of some symptoms was associated with older age, stage II, comorbidities, rural setting, and higher income. CONCLUSION: We demonstrated symptom severity was generally low and most symptoms remained stable or improved after treatment. Particular groups of patients were at greater risk for more severe and/or more persistent symptoms. Ongoing assessments and interventions to address physical and psychologic symptoms, and supportive care needs in patients with CRC during and after treatment are needed.

The impact of population-based EGFR testing in non-squamous metastatic non-small cell lung cancer in Alberta, Canada.

OBJECTIVES: While Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors have been shown to be effective in phase III randomized trials, the value of targeted therapies has been challenging to evaluate at the population-level. We examined the impact of population-level EGFR testing and treatment on survival outcomes among non-squamous metastatic Non-Small Cell Lung Cancer (NSCLC) patients. MATERIALS AND METHODS: Real-world, population-level data were collected from all de novo non-squamous metastatic NSCLC patients in Alberta, Canada from 2004 to 2020. EGFR testing data were collected through Alberta Precision Laboratories. Differences in survival rates and overall survival (OS) pre (2004-2012) and post initiation (post) (2013-2019) testing periods were evaluated using interrupted time series analyses. The impact of testing and subsequent treatment was evaluated using multivariable Cox Proportional Hazards models. RESULTS: In total, 4,578 non-squamous metastatic NSCLC patients were diagnosed pre-EGFR testing and 4,457 patients were diagnosed post-EGFR testing (2013-2019). Among patients diagnosed in the pre-EGFR testing period, the 6-month, 1-year, and 2-year survival probabilities were 0.39 (95 % CI: 0.38-0.41), 0.22 (95 % CI: 0.21-0.23), and 0.09 (95 % CI: 0.08-0.10), while the survival probabilities for patients diagnosed in the post-EGFR testing period were 0.45 (95 % CI: 0.43-0.46), 0.29 (95 % CI: 0.27-0.30), and 0.16 (95 % CI: 0.15-0.17), respectively. After adjusting for baseline patient and clinical characteristics, OS in the post-EGFR period was significantly improved compared to the pre-EGFR period (HR: 0.81; 95 % CI: 0.78-0.85). Among patients who were treated with systemic therapy, those tested for an EGFR mutation had significantly greater survival than patients who were not tested HR of 0.81 (95 % CI: 0.70-0.95). CONCLUSION: These results show the considerable impact of population-based molecular testing and subsequent targeted therapies on survival among metastatic NSCLC patients. The estimates here can be used in future studies to evaluate the population-level cost-effectiveness of testing and treatment.

Evaluating Multiple Next-Generation Sequencing-Derived Tumor Features to Accurately Predict DNA Mismatch Repair Status.

Identifying tumor DNA mismatch repair deficiency (dMMR) is important for precision medicine. Tumor features, individually and in combination, derived from whole-exome sequenced (WES) colorectal cancers (CRCs) and panel-sequenced CRCs, endometrial cancers (ECs), and sebaceous skin tumors (SSTs) were assessed for their accuracy in detecting dMMR. CRCs (n = 300) with WES, where mismatch repair status was determined by immunohistochemistry, were assessed for microsatellite instability (MSMuTect, MANTIS, MSIseq, and MSISensor), Catalogue of Somatic Mutations in Cancer tumor mutational signatures, and somatic mutation counts. A 10-fold cross-validation approach (100 repeats) evaluated the dMMR prediction accuracy for i) individual features, ii) Lasso statistical model, and iii) an additive feature combination approach. Panel-sequenced tumors (29 CRCs, 22 ECs, and 20 SSTs) were assessed for the top performing dMMR predicting features/models using these three approaches. For WES CRCs, 10 features provided >80% dMMR prediction accuracy, with MSMuTect, MSIseq, and MANTIS achieving ≥99% accuracy. The Lasso model achieved 98.3% accuracy. The additive feature approach, with three or more of six of MSMuTect, MANTIS, MSIseq, MSISensor, insertion-deletion count, or tumor mutational signature small insertion/deletion 2 + small insertion/deletion 7 achieved 99.7% accuracy. For the panel-sequenced tumors, the additive feature combination approach of three or more of six achieved accuracies of 100%, 95.5%, and 100% for CRCs, ECs, and SSTs, respectively. The microsatellite instability calling tools performed well in WES CRCs; however, an approach combining tumor features may improve dMMR prediction in both WES and panel-sequenced data across tissue types.

Transportability of Overall Survival Estimates From US to Canadian Patients With Advanced Non-Small Cell Lung Cancer With Implications for Regulatory and Health Technology Assessment.

Importance: The external validity of survival outcomes derived from clinical practice data from US patients with advanced non-small cell lung cancer (NSCLC) is not known and is of potential importance because it may be used to support regulatory decision-making and health technology assessment outside of the US. Objective: To evaluate whether overall survival (OS) estimates for a selected group of patients with advanced NSCLC from a large US clinical practice database are transportable to Canadian patients receiving the same systemic therapies. Design, Setting, and Participants: This retrospective multicenter cohort study used transportability analysis to assess whether adjustment for pretreatment characteristics of eligible patient cohorts could reliably approximate OS estimated from US-based samples to Canadian populations. A total of 17 432 eligible adult patients who were diagnosed de novo with advanced NSCLC on or after January 1, 2011, were included in the analysis and followed up until September 30, 2020. Because data on race and ethnicity were available in the US database but not the Canadian database and because racial and ethnic distribution was likely to be similar between US and Canadian patients, these characteristics were not analyzed. Exposures: Initiation of platinum-doublet chemotherapy or pembrolizumab monotherapy as first-line systemic treatment for advanced NSCLC. Main Outcomes and Measures: OS measured from the time of initiation of the respective treatment regimen. Results: Among 17 432 eligible patients, 15 669 patients from the US and 1763 patients from Canada were included in the analysis. Of those, 11 863 patients (sample size-weighted estimates of mean [SD] age, 68.0 [9.3] years; 6606 [55.7%] male; 10 100 from the US and 1763 from Canada) were included in the subset of patients with complete data for baseline covariates. A total of 13 532 US patients received first-line chemotherapy, and 2137 received first-line pembrolizumab monotherapy. Of those, 8447 patients (62.4%) in the first-line chemotherapy group and 1653 patients (77.3%) in the first-line pembrolizumab group had complete data on baseline covariates for outcome model estimation. A total of 1476 Canadian patients who received first-line chemotherapy and 287 patients who received first-line pembrolizumab monotherapy were identified from the target population. After standardization to baseline patient covariates in the Canadian cohorts, transported OS estimates revealed a less than 5% mean absolute difference from the observed OS in the target population (0.56% over 60 months of follow-up in the first-line chemotherapy group and 4.54% over 30 months of follow-up in the first-line pembrolizumab group). Negative control analysis using a mismatched outcome model revealed a 6.64% discrepancy and an incompatible survival curve shape. The results were robust to assumptions of random missingness for baseline covariates, to unadjusted differences in baseline metastases and comorbidities, and to differences in the standard of care between the US and Canada related to administration of second-line anti-programmed cell death 1 ligand 1 immunotherapy for patients who initiated first-line chemotherapy. Conclusions and Relevance: The results of this cohort study suggest that, under specific circumstances, OS estimates from US clinical practice data can be adjusted using baseline clinical characteristics to closely approximate OS in selected groups of Canadian patients with advanced NSCLC. These results may have implications for regulatory decision-making and health technology assessment in target populations outside of the US.