Delay In Diagnosis Of Cancer Research Articles

Healthcare experiences among Black and White sexual and gender minority cancer survivors: a qualitative study.

The purpose of this study was to explore healthcare experiences of Black and White sexual and gender minority (SGM) cancer survivors across the cancer care continuum. This was a qualitative analysis of two focus groups and eight individual interviews completed as part of a larger initiative using a community-engaged research approach to reduce cancer disparities in marginalized communities. There was a total of 16 participants in the study (9 were White, 7 were Black) and data were collected between 2019 and 2020. Three main themes emerged from the thematic analysis: strategically coming out, provider preferences, and health system challenges. Participants noted that they often came out through their support system, decided to come out based on the relevance of their SGM identity that they perceived, and expressed a desire for privacy. Lack of an accessible and competent PCP was tied to delayed cancer diagnosis and many participants voiced a preference for consistency when they found a provider they liked. Providers across specialties can address barriers for SGM patients by not making assumptions about patient sexual orientation or gender identity. Institutions should systematically collect sexual orientation and gender identity information. Primary care providers should be aware that due to resistance to switching from trusted providers, they may need to take greater initiative to facilitate cancer screenings for their patients when appropriate or take special care when making referrals to ensure they are using SGM-affirming providers. SGM cancer survivors often benefit from a cultivating relationship with a trusted PCP or other provider.

Abstract IA044: NCI’s persistent poverty research agenda

Abstract Poverty and its associated factors such as education, housing, employment, etc., have tremendous effects on the health of communities and their populations. An extreme form of poverty is the concept of place-based poverty, which is measured through persistent poverty areas where more than 20% of the population has lived in poverty for over 30 years. Persistent poverty areas represent an important subgroup of U.S. counties with higher disease burden and greater cancer mortality where the health consequences of elevated and continuous levels of poverty over time have not been fully investigated. The intersectionality of structural and institutional level factors along with persistent poverty results in increased cancer incidence, delayed cancer diagnosis and treatment, increased morbidity, treatment-related toxicity, and subsequently lower rates of survival. It is important to understand the interrelated effects of persistent poverty and other social, economic, and health factors, including race and ethnicity at the structural and institutional levels to implement interventions to reduce cancer disparities. The NCI seeks to eliminate cancer-related disparities in persistent poverty areas by promoting and conducting health equity research that identifies and addresses the mechanisms contributing to disparities across the cancer control continuum. There are various initiatives are underway focusing on this important research agenda. Citation Format: Amy E. Kennedy. NCI’s persistent poverty research agenda [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr IA044.

Cancer care pathways across seven countries in Europe: what are the current obstacles? And how can artificial intelligence help?

Cancer poses significant challenges for healthcare professionals across the disease pathway including cancer imaging. This study constitutes part of the user requirement definition of INCISIVE EU project. The project has been designed to explore the full potential of artificial intelligence (AI)-based technologies in cancer imaging to streamline diagnosis and management. The study aimed to map cancer care pathways (breast, prostate, colorectal and lung cancers) across INCISIVE partner countries, and identify bottle necks within these pathways. Email interviews were conducted with ten oncology specialised healthcare professionals representing INCISIVE partner countries: Greece, Cyprus, Spain, Italy, Finland, the United Kingdom (UK) and Serbia. A purposive sampling strategy was employed for recruitment and data was collected between December 2020 and April 2021. Data was entered into Microsoft Excel spreadsheet to allow content examination and comparative analysis. The analysed pathways all shared a common characteristic: inequalities in relation to delays in cancer diagnosis and treatment. All the studied countries, except the UK, lacked official national data about diagnostic and therapeutic delays. Furthermore, a considerable variation was noted regarding the availability of imaging and diagnostic services across the seven countries. Several concerns were also noted for inefficiencies/inequalities with regards to national screening for the four investigated cancer types. Delays in cancer diagnosis and treatment are an ongoing challenge and a source for inequalities. It is important to have systematic reporting of diagnostic and therapeutic delays in all countries to allow the proper estimation of its magnitude and support needed to address it. Our findings also support the orientation of the current policies towards early detection and wide scale adoption and implementation of cancer screening, through research, innovation, and technology. Technologies involving AI can have a great potential to revolutionise cancer care delivery. This study highlights the widespread delay in cancer diagnosis across Europe and supports the need for, systematic reporting of delays, improved availability of imaging services, and optimised national screening programs. The goal is to enhance cancer care delivery, encourage early detection, and implement research, innovation, and AI-based technologies for improved cancer imaging.

COVID-19 pandemic impact on screening and diagnosis of prostate cancer: a systematic review

IntroductionThe healthcare level has been greatly affected by the COVID-19 pandemic compared with before the outbreak. This study aimed to review the impact of COVID-19 on the screening and diagnosis...

MicroRNA-92b targets tumor suppressor gene FBXW7 in glioblastoma.

Glioblastoma (GBM) is a highly aggressive and lethal primary brain tumor. Despite limited treatment options, the overall survival of GBM patients has shown minimal improvement over the past two decades. Factors such as delayed cancer diagnosis, tumor heterogeneity, cancer stem cell survival, infiltrative nature of GBM cells, metabolic reprogramming, and development of therapy resistance contribute to treatment failure. To address these challenges, multitargeted therapies are urgently needed for improved GBM treatment outcomes. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Dysregulated miRNAs have been identified in GBM, playing roles in tumor initiation, progression, and maintenance. Among these miRNAs, miR-92b (miRNA-92b-3p) has been found to be overexpressed in various cancers, including GBM. However, the specific target genes of miR-92b and its therapeutic potential in GBM remain poorly explored. Samples encompassed T98G, U87, and A172 human GBM cell lines, GBM tumors from Puerto Rican patients, and murine tumors. In-situ hybridization (ISH) assessed miR-92b expression in patient tumors. Transient and stable transfections modified miR-92b levels in GBM cell lines. Real-time PCR gauged gene expressions. Caspase 3 and Trypan Blue assays evaluated apoptosis and viability. Bioinformatics tools (TargetScanHuman 8.0, miRDB, Diana tools, miRWalk) predicted targets. Luciferase assays and Western Blots validated miRNA-target interactions. A subcutaneous GBM Xenograft mouse model received intraperitoneal NC-OMIs or miR92b-OMIs encapsulated in liposomes, three-times per week for two weeks. Analysis utilized GraphPad Prism 8; statistical significance was assessed using 2-tailed, unpaired Student's t-test and two-way ANOVA as required. This study investigated the expression of miR-92b in GBM tumors compared to normal brain tissue samples, revealing a significant upregulation. Inhibition of miR-92b using oligonucleotide microRNA inhibitors (OMIs) suppressed GBM cell growth, migration, and induced apoptosis, while ectopic expression of miR-92b yielded opposite effects. Systemic administration of liposomal-miR92b-OMIs in GBM xenograft mice resulted in reductions in tumor volume and weight. Subsequent experiments identified F-Box and WD Repeat Domain Containing 7 (FBXW7) as a direct target gene of miR-92b in GBM cells. FBXW7 acts as a tumor suppressor gene in various cancer types, and analysis of patient data demonstrated that GBM patients with higher FBXW7 mRNA levels had significantly better overall survival compared to those with lower levels. Taken together, our findings suggest that the dysregulated expression of miR-92b in GBM contributes to tumor progression by targeting FBXW7. These results highlight the potential of miR-92b as a therapeutic target for GBM. Further exploration and development of miR-92b-targeted therapies may offer a novel approach to improve treatment outcomes in GBM patients.

664 Rapid-Access Head and Neck Lump Imaging Clinics Improve Compliance to the NHS Faster Diagnosis Standard, With Reduction of Head and Neck Cancer Diagnosis Times

Abstract Aim The NHS “Faster Diagnosis Standard” (FDS) recommends patients referred for suspected cancer to be diagnosed or have cancer ruled out within 28 days. Reducing time to diagnosis and treatment in head and neck cancer is associated with improved patient outcomes. Our aim was to improve compliance to the 28-day standard in a large tertiary head and neck department, by introducing a rapid-access clinic for head and neck lumps including same day ultrasound-scanning with biopsy. Method Data was collected in two rounds: 3 months before and after introduction of the rapid-access clinic in September-2022. Data collected included referral reason, time from referral to specialist review, to ultrasound, and to diagnosis. Patients not fitting agreed criteria for the clinic were excluded. Results In the first round 39 patients had a diagnosis at time of analysis; as had 13 in the second round: Initial compliance to the 28-day FDS was 33%, this increased to 85% in the second round. Median time to diagnosis was 36 days, decreasing to 12 in the second round (p-value <0.001). Median time to ultrasound was 28.5 days in the first round, decreasing to 9 in the second round (p-value <0.001). Conclusions Preliminary data shows a 53% improvement in compliance to the 28-day FDS, after introduction of the rapid-access clinic. This suggests the model could significantly improve compliance to national standards for diagnosing head and neck cancer presenting via neck lumps. This should encourage other tertiary head and neck services that creating rapid-access clinics can reduce delays in cancer diagnosis and treatment.

Delays in Cancer Diagnosis: Review of a Theoretical Literature

Cancer diagnosis which is made at a later stage than it could have been, due to various reasons such as missed or misinterpreted symptoms, delayed medical consultations, or delayed diagnostic tests, is a significant public health issue which sequentially affect the prognosis and survival rates of cancer patients. A late cancer diagnosis can have devastating consequences as many patients miss an important window of time in which cancer treatment can be most effective. As a result, time left untreated can allow cancer to grow and spread to other parts of the body, making treatment even more difficult or impossible at all. A literature review of relevant studies reveals several factors that contribute to delayed cancer diagnosis, including patient-related factors, healthcare system-related factors, and provider-related factors. Commonly and even strangely, for some type’s cancer, patients do not exhibit clear signs until later stages with which the cancer may have metastasized to other parts of the body. This can be seen when cancer screening indicated false negative results, and in this case, delayed diagnosis is unavoidable due to lack of observable symptoms.

P32 Impact of the COVID-19 pandemic on health equality in malignant melanoma diagnosis

Abstract Difficult access to care during the COVID-19 pandemic has led to a delay in some disease diagnoses. The pandemic has exacerbated pre-existing health inequalities, and the most deprived population has often been the most disproportionately affected. In this study, we investigated the impact of COVID-19 on the volume and pattern of melanoma diagnosis, to evaluate whether there is an association with the socioeconomic status of the population. Cases with newly diagnosed cutaneous melanoma from January 2019 to December 2021 were identified in a specialist multidisciplinary team-held database. Breslow thickness, pathological disease stage, patient demographics and postcodes were reviewed. In the 3-year study period, there was a total of 1910 cases. Compared with 2019 prepandemic data, there was a 31% reduction (P = 0.03) in melanoma cases diagnosed in 2020 and a 10% reduction (P = 0.09) in 2021. In 2020, stage 4 cases had a 46% increase (P = 0.031). In 2019, 7% of the most deprived population had stage 4 disease at diagnosis, which increased to 21% in 2020 (P = 0.02). COVID-19 has caused a dramatic reduction in the volume of melanoma diagnoses and an accompanying upstage of disease. Among the most deprived population in our region, they are three times more likely to receive a stage 4 diagnosis vs. before the pandemic. This suggests that the barrier to health care secondary to the pandemic is most apparent to the deprived population and probably caused a delay in cancer diagnosis among this group of patients. Health policy needs to be put in place urgently to address this health inequality, to minimize the prognostic impact on the population.

Evaluation of Leukemia and Solid Tumors in Refugee Children in Turkey: A Tertiary Center Experience

Cancer care is progressively became as a significant worldwide challenge. Wars can cause destructions and delays in cancer diagnosis and treatment of displaced people. Cancer cure rates need to be improved in indefensible populations such as refugees. In this study, we purposed to highlight the clinical peculiarities and outcomes of refugee children with cancer in our hospital. Our purpose was to present our findings and contribute to improve the health care for these children. Seventy one refugee pediatric patients admitted to the oncology and hematology units of our hospital between April 2011 and January 2019 were included in this study. The demographic characteristics of the patients at the initial diagnosis, their countries of origin, living conditions, histopathological diagnoses, treatments, relapse, and mortality data were analyzed retrospectively from the patient files. The median age of patients was 6.5±4.5 years, and the male-to-female ratio was 39/32. While 44 patients (61.9%) presented with complaints and had primary diagnoses in our hospital, the remaining 27 patients (38.1%) were diagnosed in their country and applied to our hospital for treatment. Our mean follow-up period was 18.2±18.8 months (1-90 months). As a result, 44 patients (62%) were alive and 22 (31%) were dead. The survival rate without relapse in the second year was 83.6%. Two and fiveyear survival rates were 77.5% vs. 58.1% respectively. Compared to Turkish children, lower survival rates were found in refugee children. In addition to cancer-specific factors such as tumor type and stage, some problems such as shelter, communication, adherence to treatment, and difficulties supplying medicine may be responsible for lower survival rates in refugee children. Further studies are needed to improve the survival rates of patients.

The crosstalk between Stroke and Cancer: Incidence of cancer after a first-ever cerebrovascular event in a population-based study.

To determine the cancer incidence after the first-ever cerebrovascular event (CVE) and compare it to the cancer incidence in the population from the same region. We evaluated 1069 patients with a first-ever CVE (Ischaemic or haemorrhagic stroke and Transient Ischaemic Attack) from a prospective population registry of stroke and transient focal neurological attacks, diagnosed between 2009 and 2011. We conducted a structured search to identify cancer-related variables and case-fatality for a period of 8 years following CVE. Cancer incidence in CVE patients was compared to the North Region Cancer Registry (RORENO). We found that 90/1069 (8.4%) CVE patients developed cancer after a first-ever CVE. Overall cancer annual incidence rate was higher after a CVE (820/100,000, 95%CI: 619-1020) than in general population (513/100,000, 95%CI: 508-518). In the 45-54 age group cancer incidence post-CVE was 3.2-fold (RR, 95%CI: 1.6-6.4) higher compared to the general population, decreasing gradually in older age-groups. Median time between CVE and cancer was 3.2 years (IQR = 1.4-5.2). Lower respiratory tract and colorectal were the most frequent cancer types. In univariable models, male sex (sHR = 1.78, 95%CI: 1.17-2.72, p = 0.007), tobacco use (sHR = 2.04, 95%CI: 1.31-3.18, p = 0.002) and peripheral artery disease (sHR = 2.37, 95%CI: 1.10-5.13, p = 0.028) were associated to higher cancer risk after CVE. After adjustment, tobacco use (sHR = 1.84, 95%CI: 1.08-3.14, p = 0.026) remained associated to a higher risk of cancer. At the population level, patients presenting a first-ever CVE have higher cancer incidence, that is particularly prominent in younger age-groups. Higher cancer incidence, delayed cancer diagnosis and increased mortality post-CVE warrants further research on long-term cancer surveillance in first-ever CVE survivors.

Large-scale observational prospective cohort study of a multi-cancer early detection (MCED) test in symptomatic patients referred for cancer investigation.

1501 Background: Delays in cancer diagnosis can lead to increased mortality, leading to specialized diagnostic pathways for symptomatic patients when cancer is suspected. Identification of circulating tumour DNA can stratify individuals into those more or less likely to have cancer and predict the cancer origin. This could both expedite cancer diagnosis and reduce harm and inefficient investigation in those who do not have cancer. We evaluated the performance of a next-generation sequencing MCED test (GRAIL, LLC) using cell-free DNA (cfDNA) isolated from whole blood in symptomatic patients referred to cancer diagnostic clinics by their primary care physician. Methods: Patients referred for urgent imaging, endoscopy or other diagnostic modalities to investigate symptoms suspicious for cancer were invited to take part. Participants with non-specific symptoms or being tested for lung, gynaecological, upper gastrointestinal (GI) or lower GI cancers gave a blood sample on the day they attended for urgent standard of care investigations. cfDNA was isolated from blood samples and stored until the MCED test was performed in batches, blinded to clinical outcome. The test’s predictions (cancer signal detected yes/no; predicted signal origin) were compared with the diagnosis obtained by standard care to establish the positive and negative predictive value (PPV & NPV), sensitivity and specificity across the whole study population, by referral pathway, and by presenting symptom. In addition, sensitivity was analysed by cancer site and stage. Results: 6238 participants were recruited over 5 months from the 5 clinical pathways at 44 hospital sites in England and Wales. 5461 individuals had an MCED test result and diagnostic outcome and were evaluable. Mean age was 62.1 years (SD, 13.8), 3609 (66.1%) female, 2533 (46.4%) current or former smokers. 368 (6.7%) evaluable patients had a cancer diagnosed. The MCED test detected a cancer signal in 323 cases, 244 in whom cancer was diagnosed and 79 where it was not, yielding a PPV of 75.5% (95% CI 70.5-80.1%), NPV 97.6% (97.1-98.0%), sensitivity 66.3% (61.2-71.1%), and specificity 98.4% (98.1-98.8%). Sensitivity increased with increasing age and cancer stage, from 24.2% (16.0-34.1%) in Stage I to 95.3% (88.5-98.7%) in Stage IV. Sensitivity 80.4% (66.1-90.6%) and NPV 99.1% (98.2-99.6%) were highest for patients referred with symptoms qualifying for the upper GI pathway. Conclusions: This is the first large-scale prospective evaluation of an MCED test in a symptomatic population. These data provide the basis for a prospective, interventional study in patients presenting to primary care with non-specific signs and symptoms with low, but higher than background, probability of being due to cancer. Study data are also being used to enhance the negative predictive value of the current MCED classifier for a symptomatic population. Clinical trial information: ISRCTN10226380 .

EE389 Budget Impact of a Blood-Based Auto-Antibody Test to Up-Classify Risk of Pulmonary Nodules in a US Medicare Payer Setting

An estimated 1.57 million pulmonary nodules (PNs) are detected annually in the US, a number that is increasing with more imaging and screening programs.1 Amongst these PNs, approximately 80% are initially categorized as low to moderate risk2 where many delays in cancer diagnosis occur. Workup of PNs can be essential to early diagnosis and management of non-small cell lung cancer (NSCLC). In these scenarios, a blood-based auto-antibody (AAb) test may be utilized to up-classify risk of malignancy to better inform management and treatment decisions. This study aimed to estimate the budget impact of a AAb test from a US Medicare payer perspective.

A Comparison of Risk Classification Systems of Colorectal Adenomas: A Case-Cohort Study

Because post-polypectomy surveillance uses a growing proportion of colonoscopy capacity, more targeted surveillance is warranted. We therefore compared surveillance burden and cancer detection using 3 different adenoma classification systems. In a case-cohort study among individuals who had adenomas removed between 1993 and 2007, we included 675 individuals with colorectal cancer (cases) diagnosed a median of 5.6 years after adenoma removal and 906 randomly selected individuals (subcohort). We compared colorectal cancer incidence among high- and low-risk individuals defined according to the traditional (high-risk: diameter ≥10 mm, high-grade dysplasia, villous growth pattern, or 3 or more adenomas), European Society of Gastrointestinal Endoscopy (ESGE) 2020 (high-risk: diameter ≥10 mm, high-grade dysplasia, or 5 or more adenomas), and novel (high-risk: diameter ≥20 mm or high-grade dysplasia) classification systems. For the different classification systems, we calculated the number of individuals recommended frequent surveillance colonoscopy and estimated number of delayed cancer diagnoses. Four hundred and thirty individuals with adenomas (52.7%) were high risk based on the traditional classification, 369 (45.2%) were high risk based on the ESGE 2020 classification, and 220 (27.0%) were high risk based on the novel classification. Using the traditional, ESGE 2020, and novel classifications, the colorectal cancer incidences per 100,000 person-years were 479, 552, and 690 among high-risk individuals, and 123, 124, and 179 among low-risk individuals, respectively. Compared with the traditional classification, the number of individuals who needed frequent surveillance was reduced by 13.9% and 44.2%, respectively, and 1 (3.4%) and 7 (24.1%) cancer diagnoses were delayed using the ESGE 2020 and novel classifications. Using the ESGE 2020 and novel risk classifications will substantially reduce resources needed for colonoscopy surveillance after adenoma removal.

Unmet healthcare needs among the population aged 50+ and their association with health outcomes during the COVID-19 pandemic

The COVID-19 pandemic led to unprecedented levels of subjective unmet healthcare needs (SUN). This study investigates the association between SUN in 2020 and three health outcomes in 2021—mortality, cancer, and self-assessed health (SAH), among adults aged 50 years and older, using data from the regular administration of the Survey of Health, Ageing and Retirement in Europe and from the two special waves administered in 2020 and 2021 regarding COVID-19. Three types of SUN were surveyed: care foregone due to fear of contracting COVID-19, pre-scheduled care postponed, and inability to get medical appointments or treatments demanded. We resort on the relative risk and the logistic specification to investigate the association between SUN and health outcomes. To avoid simultaneity, 1-year lagged SUN variables are used. We found a negative association between SUN and mortality. This result differs from the (scarce) previous evidence, suggesting that health systems prioritised life-threatening conditions, in the pandemic context. In line with previous studies, we obtained a positive association between SUN and worse health, in the case of cancer, though it is statistically significant only for the global measure of SUN (any reason). The higher chances of reporting cancer among those exposed to SUN might mean delayed cancer diagnosis, confirming that healthcare foregone was truly needed for a timely diagnosis. The association between SUN and poor or fair SAH is positive but not statistically significant, for the period analysed.

Association of the COVID-19 Pandemic and Changes in Patterns of Cancer-Related Mortality in the United States.

This study examined changes in patterns of cancer-related deaths during the first year of the coronavirus disease 2019 pandemic in the United States. We identified cancer-related deaths, defined as deaths attributable to cancer as the primary cause (underlying cause) or deaths with cancer documented as one of the multiple contributing factors (contributing cause) from the Multiple Cause of Death database (2015-2020). We compared age-standardized cancer-related annual and monthly mortality rates for January-December 2020 (first pandemic year) to January-December 2015-2019 (prepandemic) overall and stratified by sex, race/ethnicity, urban rural residence, and place of death. We found that the death rate (per 100,000 person-years) with cancer as the underlying cause was lower in 2020 compared with 2019 (144.1 v 146.2), continuing the past trend observed in 2015-2019. By contrast, the death rate with cancer as a contributing cause was higher in 2020 than in 2019 (164.1 v 162.0), reversing the continuously decreasing trend from 2015 to 2019. We projected 19,703 more deaths with cancer as a contributing cause than expected on the basis of historical trends. Mirroring pandemic peaks, the monthly death rates with cancer as a contributing cause first increased in April 2020 (rate ratio [RR], 1.03; 95% CI, 1.02 to 1.04), subsequently declined in May and June 2020, and then increased again each month from July through December 2020 compared with 2019, with the highest RR in December (RR, 1.07; 95% CI, 1.06 to 1.08). Death rates with cancer as the underlying cause continued to decrease in 2020 despite the increase in death rates with cancer as a contributing cause in 2020. Ongoing monitoring of long-term cancer-related mortality trends is warranted to assess effects of delays in cancer diagnosis and receipt of care during the pandemic.

Missing melanomas in England during the COVID-19 pandemic: 2,485 fewer melanoma diagnoses in 2020 than in 2019.

Malignant melanoma (MM) can have a high mortality if diagnosed late. Three waves of COVID-19 in 2020–21 led to periods of reduced healthcare provision in England. Although most cancer services were maintained, factors such as patient anxiety, staff and facility redeployment, and staff sickness delayed cancer diagnoses. We aimed to investigate the effect of the COVID-19 pandemic on MM diagnoses and stage at presentation in England

Delayed cancer diagnosis in the pregnant patient: navigating a complex medical and ethical dilemma.

Prompt diagnosis of cancer in pregnancy is necessary to ensure timely management and improve outcomes. However, there are a several reasons why diagnosis may be delayed in pregnancy. Three major contributors to delayed diagnosis and treatment are patient delay, provider delay, and referral delay. This article aims to (1) increase physician awareness of this problem by providing a detailed review of the main culprits of delayed diagnosis and treatment of cancer in the pregnant patient, (2) discuss the complex ethical issues at hand in these cases, and (3) provide suggestions on how to better address such cases with the goal of improving patient outcomes.

Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals

Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but harms could be reduced and cost-effectiveness improved by reusing the LDCT image in conjunction with deep learning or statistical models to identify low-risk individuals for biennial screening. To identify low-risk individuals in the National Lung Screening Trial (NLST) and estimate, had they been assigned a biennial screening, how many lung cancers would have been delayed 1 year in diagnosis. This diagnostic study included participants with a presumed nonmalignant lung nodule in the NLST between January 1, 2002, and December 31, 2004, with follow-up completed on December 31, 2009. Data were analyzed for this study from September 11, 2019, to March 15, 2022. An externally validated deep learning algorithm that predicts malignancy in current lung nodules using LDCT images (Lung Cancer Prediction Convolutional Neural Network [LCP-CNN]; Optellum Ltd) was recalibrated to predict 1-year lung cancer detection by LDCT for presumed nonmalignant nodules. Individuals with presumed nonmalignant lung nodules were hypothetically assigned annual vs biennial screening based on the recalibrated LCP-CNN model, Lung Cancer Risk Assessment Tool (LCRAT + CT [a statistical model combining individual risk factors and LDCT image features]), and the American College of Radiology recommendations for lung nodules, version 1.1 (Lung-RADS). Primary outcomes included model prediction performance, the absolute risk of a 1-year delay in cancer diagnosis, and the proportion of people without lung cancer assigned a biennial screening interval vs the proportion of cancer diagnoses delayed. The study included 10 831 LDCT images from patients with presumed nonmalignant lung nodules (58.7% men; mean [SD] age, 61.9 [5.0] years), of whom 195 were diagnosed with lung cancer from the subsequent screen. The recalibrated LCP-CNN had substantially higher area under the curve (0.87) than LCRAT + CT (0.79) or Lung-RADS (0.69) to predict 1-year lung cancer risk (P < .001). If 66% of screens with nodules were assigned to biennial screening, the absolute risk of a 1-year delay in cancer diagnosis would have been lower for recalibrated LCP-CNN (0.28%) than LCRAT + CT (0.60%; P = .001) or Lung-RADS (0.97%; P < .001). To delay only 10% of cancer diagnoses at 1 year, more people would have been safely assigned biennial screening under LCP-CNN than LCRAT + CT (66.4% vs 40.3%; P < .001). In this diagnostic study evaluating models of lung cancer risk, a recalibrated deep learning algorithm was most predictive of 1-year lung cancer risk and had least risk of 1-year delay in cancer diagnosis among people assigned biennial screening. Deep learning algorithms could prioritize people for workup of suspicious nodules and decrease screening intensity for people with low-risk nodules, which may be vital for implementation in health care systems.

Patients With Limited English Proficiency: A Challenge for Oncology Nursing Providers.

Limited English proficiency (LEP) is a limited ability to read, write, speak, and understand English. About 145,000 individuals with LEP will be diagnosed with a new cancer annually, and English remains the dominant language spoken in the U.S. medical system. The goal of this article is to discuss the issues faced by patients with LEP and cancer who are unable to communicate effectively with oncology providers. This overview used published U.S. government statistics, information from consensus and policy organizations, and clinical studies published between 2017 and 2022. Federal laws prohibit discrimination based on immigration status. People with LEP experience delayed cancer diagnoses and often receive inadequate treatment. Patients with LEP often have limited understanding of the medical system and do not receive language-concordant information about their cancer and treatment options.

Applications of different machine learning approaches in prediction of breast cancer diagnosis delay.

The increasing rate of breast cancer (BC) incidence and mortality in Iran has turned this disease into a challenge. A delay in diagnosis leads to more advanced stages of BC and a lower chance of survival, which makes this cancer even more fatal. The present study was aimed at identifying the predicting factors for delayed BC diagnosis in women in Iran. In this study, four machine learning methods, including extreme gradient boosting (XGBoost), random forest (RF), neural networks (NNs), and logistic regression (LR), were applied to analyze the data of 630 women with confirmed BC. Also, different statistical methods, including chi-square, p-value, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC), were utilized in different steps of the survey. Thirty percent of patients had a delayed BC diagnosis. Of all the patients with delayed diagnoses, 88.5% were married, 72.1% had an urban residency, and 84.8% had health insurance. The top three important factors in the RF model were urban residency (12.04), breast disease history (11.58), and other comorbidities (10.72). In the XGBoost, urban residency (17.54), having other comorbidities (17.14), and age at first childbirth (>30) (13.13) were the top factors; in the LR model, having other comorbidities (49.41), older age at first childbirth (82.57), and being nulliparous (44.19) were the top factors. Finally, in the NN, it was found that being married (50.05), having a marriage age above 30 (18.03), and having other breast disease history (15.83) were the main predicting factors for a delayed BC diagnosis. Machine learning techniques suggest that women with an urban residency who got married or had their first child at an age older than 30 and those without children are at a higher risk of diagnosis delay. It is necessary to educate them about BC risk factors, symptoms, and self-breast examination to shorten the delay in diagnosis.