Highly sensitive lanthanide complex as a probe for l-kynurenine: A cancer biomarker.

A lanthanide complex based on europium (Eu) and chelidamic acid was synthesized (Eu-CHE) and characterized. The complex Eu-CHE exhibited intense luminescence at 615 nm under excitation at 300 nm and was further investigated for highly sensitive turn-off detection of l-kynurenine (l-kyn), a cancer biomarker. The probe detected l-kyn linearly from 6 nM to 0.2 µM with a limit of detection and limit of quantification of 1.37 and 4.57 nM, respectively. The probe was investigated for selectivity towards l-kyn among co-existing amino acids and further extended for detecting l-kyn from human serum and urine samples. A low-cost paper strip-based sensing platform was also developed for the visual detection of l-kyn.

Risk Burden of Cancer in Patients Treated With Abbreviated Dual Antiplatelet Therapy After PCI: Analysis of Multicenter Controlled High-Bleeding Risk Trials.

BACKGROUND: Oncological patients with coronary artery disease face an elevated risk of hemorrhagic and ischemic events following percutaneous coronary intervention. Despite medical guidelines recommending minimal dual antiplatelet therapy (DAPT) duration for patients with cancer, dedicated data on abbreviated DAPT in this population is lacking. This study aims to evaluate the occurrence of ischemic and hemorrhagic events in patients with cancer compared with other high-bleeding risk individuals. METHODS: Patient-level data from 4 high-bleeding risk coronary drug-eluting stent studies (ONYX One, LEADERS FREE, LEADERS FREE II, and SENIOR trials) treated with short DAPT were analyzed. The comparison focused on patients with high-bleeding risk with and without cancer, assessing 1-year rates of net adverse clinical events (all-cause death, myocardial infarction, stroke, revascularization, and Bleeding Academic Research Consortium [BARC] types 3 to 5 bleeding) and major adverse clinical events (all-cause death, myocardial infarction, stroke). RESULTS: A total of 5232 patients were included, of whom 574 individuals had cancer, and 4658 were at high-bleeding risk without previous cancer. Despite being younger with fewer risk factors, patients with cancer had higher net adverse clinical event (HR, 1.25; P=0.01) and major adverse clinical event (HR, 1.26; P=0.02), primarily driven by all-cause mortality and major bleeding (BARC 3-5), but not myocardial infarction, stroke, stent thrombosis, or repeat revascularization. Cancer was an independent predictor of net adverse clinical event (P=0.005), major adverse clinical event (P=0.01), and major bleeding (P=0.03). CONCLUSIONS: The present work is the first report on abbreviated DAPT dedicated to patients with cancer. Cancer is a major marker of adverse outcomes and these events had high lethality. Despite short DAPT, patients with cancer experienced higher rates of major bleeding compared with patients without cancer with high-bleeding risk, which occurred mainly after DAPT discontinuation. These findings reinforce the need for a more detailed and individualized stratification of those patients. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03344653, NCT01623180, NCT02843633, NCT0284.

Performance of Distress Thermometer: A Study among Cancer Patients.

BACKGROUND: The Distress Thermometer accompanied with Problems List is a commonly used screening tool for psychosocial distress. However, it's cut-off score, performance and risk factors for psychosocial distress varies among studies. This is the first study conducted in Nepal to investigate the Distress Thermometer's screening properties, its optimal cut-off score and evaluating the prevalence of psychosocial distress and its risk factors. METHODS: This cross-sectional study enrolled 162 heterogeneous cancer patients. The English form of the Distress Thermometer was translated to Nepali using a forward and backward translation method. Questionnaires including socio-demographic, clinical characteristics, the Hospital Anxiety and Depression Scale and Distress Thermometer accompanied with Problems List were filled. Receiver Operating Characteristic analysis of distress thermometer scores was evaluated against Hospital Anxiety and Depression Scale-Total (≥15). An Area Under the Curve, sensitivity, specificity, positive predictive value and negative predictive value were calculated at each Distress Thermometer cut-off score. RESULTS: Receiver Operating Characteristic analysis showed an excellent discriminating performance (Area Under the Curve =87.4%). A cut-off score of 4 on Distress Thermometer was established and it yielded sensitivity (88.9%), specificity (71.1%), positive predictive value (75.4%) and negative predictive value (86.5%) respectively. Furthermore, 55.6% of participants were distressed and emotional problems (odd ratio = 28.00), practical problems (odd ratio = 12.152) and physical problems (odd ratio = 2.397) were found to be significant risk factors for PD. CONCLUSIONS: PD is a global burden in cancer patients. The DT with a cut-off score of 4 accompanied with PL is valid instrument for screening PD in Nepali cancer patients. PL identified the problems that causes of PD.

Impact of the COVID-19 pandemic in childhood and adolescent cancer care in northern Tanzania: a cross-sectional study.

INTRODUCTION: The SARS-CoV-2 (COVID-19) pandemic has strained healthcare systems and presented unique challenges for children requiring cancer care, particularly in low- and middle-income countries. This study aimed to assess the impact of the COVID-19 pandemic on access to cancer care for children and adolescents in Northern Tanzania. METHODS: In this cross-sectional study, we assessed the demographic and clinical characteristics of 547 pediatric and adolescent cancer patients (ages 0-19 years old) between 2016 and 2022 using the population-based Kilimanjaro Cancer Registry (KCR). We categorized data into pre-COVID-19 (2016-2019) and COVID-19 (2020-2022) eras, and performed descriptive analyses of diagnostic, treatment, and demographic information. A secondary analysis was conducted on a subset of 167 patients with stage of diagnosis at presentation. RESULTS: Overall admissions nearly doubled during the pandemic (n = 190 versus 357). The variety of diagnoses attended at KCMC increased during the pandemic, with only five groups of diseases reported in 2016 to twelve groups of diseases in 2021. Most patients were diagnosed at a late stage (stage III or IV) across eras, with the proportion of under-five years old patients increasing late-diagnoses from 29.4% (before the pandemic), 52.8% (during the pandemic), when compared to the overall cohort. Around 95% of children in this age category reported late-stage diagnosis during the pandemic. Six out of the twelve cancer site groups also reported an increase in late-stage diagnosis. During the pandemic, the proportion of children receiving surgery increased from 15.8 to 30.8% (p < 0.001). CONCLUSION: Childhood and adolescent cancer care changed in Northern Tanzania during the COVID-19 pandemic, with increased late-stage diagnoses presentations among younger patients and the increased use of surgical therapies in the context of a growing practice. Understanding the impact of the COVID-19 pandemic on pediatric and adolescent cancer care can help us better adapt healthcare systems and interventions to the emerging needs of children and adolescents with cancer in the midst of a health crisis.

A Self-Powered Lactate Sensor Based on the Piezoelectric Effect for Assessing Tumor Development.

The build-up of lactate in solid tumors stands as a crucial and early occurrence in malignancy development, and the concentration of lactate in the tumor microenvironment may be a more sensitive indicator for analyzing primary tumors. In this study, we designed a self-powered lactate sensor for the rapid analysis of tumor samples, utilizing the coupling between the piezoelectric effect and enzymatic reaction. This lactate sensor is fabricated using a ZnO nanowire array modified with lactate oxidase (LOx). The sensing process does not require an external power source or batteries. The device can directly output electric signals containing lactate concentration information when subjected to external forces. The lactate concentration detection upper limit of the sensor is at least 27 mM, with a limit of detection (LOD) of approximately 1.3 mM and a response time of around 10 s. This study innovatively applied self-powered technology to the in situ detection of the tumor microenvironment and used the results to estimate the growth period of the primary tumor. The availability of this application has been confirmed through biological experiments. Furthermore, the sensor data generated by the device offer valuable insights for evaluating the likelihood of remote tumor metastasis. This study may expand the research scope of self-powered technology in the field of medical diagnosis and offer a novel perspective on cancer diagnosis.

A comprehensive exploration of twist1 to identify a biomarker for tumor immunity and prognosis in pan-cancer.

Twist1 has been identified as a critical gene in tumor, but current study of this gene remains limitative. This study aims to investigate its roles and potential mechanisms across pan-cancer. The study used various databases and computational techniques to analyze twist's RNA expression, clinical data, gene mutations, tumor stemness, tumor microenvironment, immune regulation. Furthermore, the experimental method of fluorescence staining was carried out to identify twist1 expression in various tumor masses. After analyzing the protein-protein interaction of TWIST, enrichment analysis and predictive potential drugs were performed, and molecular docking was conducted to validate. We found that twist1 expression was significantly higher in various types of cancer and associated with tumor stage, grade, and poor prognosis in multiple cancers. Differential expression of twist1 was linked to gene mutation, RNA modifications, and tumor stemness. Additionally, twist1 expression was positively associated with tumor immunoregulation and immune checkpoint. Salinomycin, klugline, isocephaelince, manassantin B, and pimonidazole are predictive potential drugs targeting TWIST1. This study revealed that twist1 plays an important role in tumor, and might be a curial marker in tumor diagnose and prognosis. The study also highlighted twist1 as a promising therapeutic target for cancer treatment and provided a foundation for future research.

Utilizing geospatial artificial intelligence to map cancer disparities across health regions.

We have developed an innovative tool, the Intelligent Catchment Analysis Tool (iCAT), designed to identify and address healthcare disparities across specific regions. Powered by Artificial Intelligence and Machine Learning, our tool employs a robust Geographic Information System (GIS) to map healthcare outcomes and disease disparities. iCAT allows users to query publicly available data sources, health system data, and treatment data, offering insights into gaps and disparities in diagnosis and treatment paradigms. This project aims to promote best practices to bridge the gap in healthcare access, resources, education, and economic opportunities. The project aims to engage local and regional stakeholders in data collection and evaluation, including patients, providers, and organizations. Their active involvement helps refine the platform and guides targeted interventions for more effective outcomes. In this paper, we present two sample illustrations demonstrating how iCAT identifies healthcare disparities and analyzes the impact of social and environmental variables on outcomes. Over time, this platform can help communities make decisions to optimize resource allocation.

The value of intratumoral microbiota in the diagnosis and prognosis of tumors.

Intratumoral microbiota (ITM) are microorganisms present in tumor cells. ITM participate in tumor development by affecting tumor cells directly and the tumor microenvironment (TME), indirectly. Alterations in ITM instigate changes in tumor DNA, activate oncogenic pathways, induce tumor inflammatory responses, disrupt normal immune activity, and facilitate the secretion of effectors leading to tumor progression, metastasis, or diminished therapeutic effects. ITM varies significantly in different types of cancer cells and disease states. The presence of certain ITM serves as a predictor of various disease states. Thus, ITM predicts tumorigenesis, tumor grade, treatment efficacy, and prognosis, making it a potential tumor biomarker. The present study aimed to determine the mechanisms by which ITM affects tumor development, especially through the TME; highlight the significant potential of ITM in enhancing tumor diagnosis and prognosis; and outline future directions for ITM research, with a focus on the development of innovative tumor markers.

The 3D Revolution in Cancer Discovery.

SUMMARY: The transition from 2D to 3D spatial profiling marks a revolutionary era in cancer research, offering unprecedented potential to enhance cancer diagnosis and treatment. This commentary outlines the experimental and computational advancements and challenges in 3D spatial molecular profiling, underscoring the innovation needed in imaging tools, software, artificial intelligence, and machine learning to overcome implementation hurdles and harness the full potential of 3D analysis in the field.

Supporting the decision to perform molecular profiling for cancer patients based on routinely collected data through the use of machine learning.

BACKGROUND: Personalized medicine offers targeted therapy options for cancer treatment. However, the decision whether to include a patient into next-generation sequencing (NGS) testing is not standardized. This may result in some patients receiving unnecessary testing while others who could benefit from it are not tested. Typically, patients who have exhausted conventional treatment options are of interest for consideration in molecularly targeted therapy. To assist clinicians in decision-making, we developed a decision support tool using routine data from a precision oncology program. METHODS: We trained a machine learning model on clinical data to determine whether molecular profiling should be performed for a patient. To validate the model, the model's predictions were compared with decisions made by a molecular tumor board (MTB) using multiple patient case vignettes with their characteristics. RESULTS: The prediction model included 440 patients with molecular profiling and 13,587 patients without testing. High area under the curve (AUC) scores indicated the importance of engineered features in deciding on molecular profiling. Patient age, physical condition, tumor type, metastases, and previous therapies were the most important features. During the validation MTB experts made the same decision of recommending a patient for molecular profiling only in 10 out of 15 of their previous cases but there was agreement between the experts and the model in 9 out of 15 cases. CONCLUSION: Based on a historical cohort, our predictive model has the potential to assist clinicians in deciding whether to perform molecular profiling.

Diagnosis of malignant body fluids via cancer-universal methylation in cell-free DNA.

BACKGROUNDDifferentiating malignant from nonmalignant body fluids remains a clinical challenge because of the unsatisfying performance of conventional cytology. We aimed to improve the sensitivity and ubiquity of cancer cell detection by assaying universal cancer-only methylation (UCOM) markers in supernatant cell-free DNA (cfDNA).METHODSAn observational prospective cohort including 1,321 nonmalignant and malignant body fluids of multiple cancers was used to develop and validate a cfDNA UCOM methylation diagnostic assay. All samples were divided into 2 portions for cytology and supernatant cfDNA methylation analysis.RESULTSThe significant hypermethylation of a potentially novel UCOM marker, TAGMe, together with the formerly reported PCDHGB7, was identified in the cfDNA of malignant body fluid samples. The combined model, cell-free cancer-universal methylation (CUE), was developed and validated in a prospective multicancer cohort with markedly elevated sensitivity and specificity, and was further verified in a set containing additional types of malignant body fluids and metastases. In addition, it remained hypersensitive in detecting cancer cells in cytologically negative malignant samples.CONCLUSIONcfDNA methylation markers are robust in detecting tumor cells and are applicable to diverse body fluids and tumor types, providing a feasible complement to current cytology-based diagnostic analyses.TRIAL REGISTRATIONThis study was registered at Chictr.org.cn (ChiCTR2200060532).FUNDINGNational Natural Science Foundation of China (32270645, 31872814, 32000505, 82170088), the National Key R&D Program of Ningxia Hui Autonomous region (2022BEG01003), Shanghai Municipal Key Clinical Specialty (shslczdzk02201), Science and Technology Commission of Shanghai Municipality (20DZ2261200, 20DZ2254400), and Major Special Projects of Basic Research of Shanghai Science and Technology Commission (18JC1411101).

Have the recent advancements in cancer therapy and survival benefitted patients of all age groups across the Nordic countries? NORDCAN survival analyses 2002-2021.

BACKGROUND: Since the early 2000s, overall and site-specific cancer survival have improved substantially in the Nordic countries. We evaluated whether the improvements have been similar across countries, major cancer types, and age groups. MATERIAL AND METHODS: Using population-based data from the five Nordic cancer registries recorded in the NORDCAN database, we included a cohort of 1,525,854 men and 1,378,470 women diagnosed with cancer (except non-melanoma skin cancer) during 2002-2021, and followed for death until 2021. We estimated 5-year relative survival (RS) in 5-year calendar periods, and percentage points (pp) differences in 5-year RS from 2002-2006 until 2017-2021. Separate analyses were performed for eight cancer sites (i.e. colorectum, pancreas, lung, breast, cervix uteri, kidney, prostate, and melanoma of skin). RESULTS: Five-year RS improved across nearly all cancer sites in all countries (except Iceland), with absolute differences across age groups ranging from 1 to 21 pp (all cancer sites), 2 to 20 pp (colorectum), -1 to 36 pp (pancreas), 2 to 28 pp (lung), 0 to 9 pp (breast), -11 to 26 pp (cervix uteri), 2 to 44 pp (kidney), -2 to 23 pp (prostate) and -3 to 30 pp (skin melanoma). The oldest patients (80-89 years) exhibited lower survival across all countries and sites, although with varying improvements over time. INTERPRETATION: Nordic cancer patients have generally experienced substantial improvements in cancer survival during the last two decades, including major cancer sites and age groups. Although survival has improved over time, older patients remain at a lower cancer survival compared to younger patients.

Capacidad pronóstica del PIV (pan-immune-inflammation value) en pacientes con carcinoma escamoso de cabeza y cuello / Prognostic capacity of PIV (pan-immune-inflammation value) in patients with head and neck squamous cell carcinoma

Introducción: El PIV (pan-immune-inflammation value), un índice que resulta del cociente (neutrófilos×monocitos×plaquetas) / linfocitos, ha sido propuesto como un biomarcador con capacidad pronóstica en diferentes modelos tumorales. El objetivo del presente estudio es analizar la capacidad pronóstica del PIV en pacientes con carcinoma escamoso de cabeza y cuello. Pacientes y métodos: Estudio retrospectivo de 1.187 pacientes con carcinoma escamoso de cabeza y cuello tratados en nuestro centro durante el periodo 2000-2017. Se obtuvo el valor del PIV a partir de un análisis realizado en un intervalo inferior a las 3 semanas previas al inicio del tratamiento. Resultados: El valor del PIV se relacionó de forma significativa con el consumo de tóxicos (p=0,001), la localización del tumor (0,0001), la extensión tumoral (0,0001), y el grado histológico (0,016). Mediante un análisis de partición recursiva se definieron 4 categorías en función del valor del PIV: categoría i: PIV<136,3 (n=118; 9,9%), categoría ii: PIV 136,3-451,1 (n=594, 50,0%); categoría iii: PIV 451,1-1.141,2 (n=357; 30,1%); categoría iv: PIV>1.141,2 (n=118; 9,9%). Se pudo observar una reducción ordenada y significativa de la supervivencia específica a medida que se incrementaba la categoría en el valor del PIV. Esta disminución en la supervivencia se produjo de forma independiente al tipo de tratamiento, la extensión del tumor, o la localización del tumor primario. La categoría en el valor del PIV se relacionó de forma significativa con la supervivencia específica en un estudio multivariable. Conclusiones: El PIV es un biomarcador con capacidad pronóstica en los pacientes con carcinoma escamoso de cabeza y cuello.(AU)

Introduction: The pan-immune-inflammation value (PIV), an index that results from the following ratio: (neutrophils×monocytes×platelets) / lymphocytes, has been proposed as a prognostic biomarker in different tumor models. The aim of this study is to analyze the prognostic capacity of PIV in patients with head and neck squamous cell carcinoma. Patients and methods: Retrospective study of 1,187 patients with head and neck squamous cell carcinoma treated at our center between 2000-2017. PIV value was obtained from an analysis performed within 3 weeks prior to the start of treatment. Results: PIV value was significantly associated with toxic consumption (0.001), tumor location (0.0001), tumor extension (0.0001), and histological grade (0.016). Four categories were defined based on PIV value using a recursive partitioning analysis: category i: PIV<136.3 (n=118, 9.9%), category ii: PIV 136.3-451.1 (n=594, 50.0%), category iii: PIV 451.1-1,141.2 (n=357, 30.1%), and category iv: PIV>1,141.2 (n=118, 9.9%). A significant and ordered decrease in disease-specific survival was observed as the PIV category increased. This decrease in survival was independent of the type of treatment, tumor extension, or location of the primary tumor. The PIV category was an independent prognostic factor of disease-specific survival in a multivariable study. Conclusions: PIV is a prognostic biomarker in patients with head and neck squamous cell carcinoma.(AU)

Using emulated clinical trials to investigate the risk of being diagnosed with psychiatric ill health following the cancer diagnosis of a sibling.

BACKGROUND: The sibling bond is often the longest relationship in an individual's life, spanning both good and bad times. Focusing on the latter, we investigated whether a cancer diagnosis in one adult sibling is predictive of psychiatric illness in the other, and if any such effect differs according the 'sociodemographic closeness' between the siblings in terms of sex, age, education, marital status and residence. METHODS: We used hospital records to identify psychiatric diagnoses (2005-2019) in a Swedish total-population cohort born in 1953, and cancer diagnoses (2005-2017) in their full siblings. By means of emulated clinical trials, the cohort member's risk of a diagnosis within two years following a first exposure (or non-exposure) to a sibling's cancer was analyzed through Cox regression. RESULTS: Exposed cohort members had a higher risk of psychiatric diagnosis than unexposed (HR = 1.15; CI: 1.08-1.23), with men displaying a higher risk (1.19; CI: 1.09-1.31) than women (HR = 1.11; CI: 1.01-1.22). Sub-analyses of the exposed group showed that women with a cancer-stricken sister had a higher risk of adverse psychiatric outcomes (HR = 1.31; CI: 1.07-1.61) than women with a cancer-stricken brother. Furthermore, unmarried cohort members ran a higher risk, both when the cancer-stricken sibling was married (HR = 2.03; CI: 1.67-2.46) and unmarried (HR = 2.61; CI: 2.16-3.15), than in cases where both siblings were married. No corresponding difference were detected for 'closeness' in age, education and residence. CONCLUSIONS: In line with theories of linked lives, our findings suggest that negative events in one sibling's life tend to 'spill over' on the other sibling's wellbeing, at least during the 15-year-long period leading up to retirement age.

Proposal of model for personalized early adapted cancer screening in people living with HIV: experience of "Gaetano Martino" Hospital University of Messina.

Human immunodeficiency virus (HIV) infection has historically been related to the development of specific cancers, some of which are so closely linked to the infection, such as Kaposi's Sarcoma (KS), that they have earned the name Acquired Immuno-Deficiency Syndrome (AIDS)-defining cancers (ADCs). While the development of antiretroviral therapy (ART) has decreased the incidence of AIDS-defining cancers, the resulting aging of people living with HIV (PLWH) highlighted an increased occurrence of other forms of cancer. At the "Gaetano Martino" hospital in Messina, we developed a multidisciplinary approach by creating a bridge between the Oncology Unit and the Infectious Diseases Unit to carry out screening and a more rapid diagnostic and therapeutic journey for cancers in PLWH. The goal is to improve the diagnosis of various types of cancer by involving other professionals, such as gastroenterologists and gynecologists, to ensure faster access to treatment and, therefore, a greater chance of survival. In addition, our multidisciplinary approach has also included vaccine screening, offered by the "Gaetano Martino" hospital and useful for preventing the development of specific forms of cancer in the entire population and particularly in PLWH.

Serum micro-RNAs with mutation-targeted RNA modification: a potent cancer detection tool constructed using an optimized machine learning workflow.

RNA modifications affect fundamental biological processes and diseases and are a research hotspot. Several micro-RNAs (miRNAs) exhibit genetic variant-targeted RNA modifications that can greatly alter their biofunctions and influence their effect on cancer. Therefore, the potential role of these miRNAs in cancer can be implicated in new prevention and treatment strategies. In this study, we determined whether RMvar-related miRNAs were closely associated with tumorigenesis and identified cancer-specific signatures based on these miRNAs with variants targeting RNA modifications using an optimized machine learning workflow. An effective machine learning workflow, combining least absolute shrinkage and selection operator analyses, recursive feature elimination, and nine types of machine learning algorithms, was used to screen candidate miRNAs from 504 serum RMvar-related miRNAs and construct a diagnostic signature for cancer detection based on 43,047 clinical samples (with an area under the curve value of 0.998, specificity of 93.1%, and sensitivity of 99.3% in the validation cohort). This signature demonstrated a satisfactory diagnostic performance for certain cancers and different conditions, including distinguishing early-stage tumors. Our study revealed the close relationship between RMvar-related miRNAs and tumors and proposed an effective cancer screening tool.

Relevance of blood tumor markers in inpatients with significant involuntary weight loss and elevated levels of inflammation biomarkers.

PURPOSE: To assess the diagnostic performance of a panel of standard tumor markers (TMs) in patients hospitalized with significant involuntary weight loss (IWL) and elevated levels of inflammation biomarkers, and a combination of the TM panel and the finding of the computed tomography (CT) scan. METHODS: We conducted a retrospective study in the internal medicine department at Amiens-Picardie University Medical Center (Amiens, France) between January 1st, 2015, and November 1st, 2021. The inclusion criteria were age 18 or over, significant IWL (≥ 5 kg over 6 months), elevated inflammation biomarkers (e.g. C-reactive protein), and assay data on two or more standard TMs (carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19 - 9, CA 15 - 3, CA 125, neuron-specific enolase (NSE), alpha-fetoprotein (AFP), calcitonin, and prostate-specific antigen (PSA)). The result of each TM assay was interpreted qualitatively (as positive or negative), according to our central laboratory's usual thresholds. RESULTS: Cancer was diagnosed in 50 (37.0%) of the 135 patients included. Positivity for one or more TMs had a positive predictive value (PPV) of 0.55 [0.43-0.66], and a negative predictive value (NPV) of 0.84 [0.75-0.93] for cancer diagnosis. When combined with the presence of suspicious CT findings (e.g. a mass, enlarged lymph nodes and/or effusion), positivity for one or more TMs had a PPV of 0.92 [0.08-0.30]. In the absence of suspicious CT findings, a fully negative TM panel had an NPV of 0.96 [0.89-1.00]. CONCLUSION: A negative TM panel argues against the presence of a cancer, especially in the absence of suspicious CT findings.

Development and Evaluation of a Multisource Approach to Extend Mortality Follow-Up for Older Adults With Advanced Cancer Enrolled in Randomized Trials.

PURPOSE: Mortality data can complement primary end points from cancer clinical trials. Yet, identifying deaths after trial completion is challenging, as timely and comprehensive vital status data are unavailable in the United States. We developed and evaluated a multisource approach to capture death data after clinical trial completion. METHODS: Individuals age 70 years and older with incurable solid tumors or lymphoma and ≥1 aging-related condition were enrolled from October 2014 to March 2019 (ClinicalTrials.gov identifier: NCT02107443 and NCT02054741). Participants provided consent to link trial information to external sources. We developed a stepped approach for extended death capture using (1) active trial follow-up up to 1 year, (2) linkage to the National Death Index (NDI), and (3) obituary searches, thus generating a 5-year survival curve. In a random sample of 50 participants who died during trial follow-up, we estimated sensitivity of death data using NDI and obituary sources and computed survival times by data source. RESULTS: The two trials enrolled 1,169 participants; mean age was 76 years; 46% were female; and gastrointestinal cancer (30%) and lung cancer (26%) were the most common cancer types. Across data sources, maximum follow-up was >7 years; 5-year survival was 18%. In total, there were 841 deaths: 603 identified during trial follow-up; 199 from the NDI; and 39 from obituary searches. The sensitivity for death capture was 92% for the NDI and 94% for the obituary searches compared with the trial data, and computed survival times were similar across data sources. CONCLUSION: Extending clinical trial mortality follow-up through linkage with external data sources was feasible and accurate. Future cancer clinical trials should collect necessary consent and patient identifiers for vital status linkages that can enhance understanding of longer-term outcomes.