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Cancers
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Cancer Detection in Primary Care
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Cancer Detection in Primary Care

A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 31504

Special Issue Editors

Dr. Garth Funston

E-Mail Website
Guest Editor
The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
Interests: ovarian cancer; symptoms; early detection; risk assessment; prediction model; triage tool; ovarian cancer symptoms; primary care cancer research
Prof. Dr. Fiona M. Walter

E-Mail Website
Guest Editor
1. Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AB, UK
2. The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
Interests: primary care medicine; primary care cancer research; cancer detection and diagnosis; cancer screening; cancer genomics and primary care; risk assessment; medical education

Special Issue Information

Dear Colleagues, 

The majority of patients with cancer are diagnosed after presenting symptomatically to primary care. Earlier identification of cancer in primary care has the potential to improve patient outcomes, including survival. However, it poses unique challenges due to the low prevalence of many cancers in the primary care setting, the non-specific nature of presenting symptoms, and the limited access to cancer investigations. In addition, primary care practitioners must balance the need for timely cancer detection against the potential harms of over-investigation and, for some cancers, over-diagnosis.

In recent years studies have dramatically improved our understanding of how patients with cancer present in primary care, and innovations—including new tests, prediction models and dedicated cancer pathways—have been implemented to improve the diagnostic process. This Special Issue seeks to bring together high-quality original research and review articles which focus on the timely detection of cancer within primary care.

Topics of interest include but are not limited to:

  • Evaluation of cancer tests
  • Clinical prediction models
  • AI and machine learning approaches to cancer detection
  • Evaluation of cancer diagnostic pathways
  • Educational interventions
  • Health economic assessments
  • Identification of barriers to cancer detection

Dr. Garth Funston
Prof. Dr. Fiona M. Walter
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • primary care
  • early detection
  • cancer detection
  • diagnostic pathway
  • symptomatic cancer

Published Papers (15 papers)

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Research

14 pages, 5920 KiB  
Article
Mobilization of Circulating Tumor Cells after Short- and Long-Term FOLFIRINOX and GEM/nab-PTX Chemotherapy in Xenograft Mouse Models of Human Pancreatic Cancer
by Yukako Ito, Shinji Kobuchi, Amiri Kawakita, Kazuki Tosaka, Yume Matsunaga, Shoma Yoshioka, Shizuka Jonan, Kikuko Amagase, Katsunori Hashimoto, Mitsuro Kanda, Takuya Saito and Hayao Nakanishi
Cancers 2023, 15(22), 5482; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15225482 - 20 Nov 2023
Viewed by 938
Abstract
Mobilization of CTCs after various types of therapy, such as radiation therapy, has been reported, but systematic study of CTCs after chemotherapy remained quite limited. In this study, we sequentially examined CTC numbers after single-dose and repetitive-dose chemotherapy, including FORFIRINOX (FFX) and Gemcitabine [...] Read more.
Mobilization of CTCs after various types of therapy, such as radiation therapy, has been reported, but systematic study of CTCs after chemotherapy remained quite limited. In this study, we sequentially examined CTC numbers after single-dose and repetitive-dose chemotherapy, including FORFIRINOX (FFX) and Gemcitabine and nab-Paclitaxel (GnP) using two pancreatic cancer xenograft models. CTC was detected by the immunocytology-based microfluidic platform. We further examined the dynamic change in the histology of primary tumor tissues during chemotherapy. We confirmed a transient increase in CTCs 1–2 weeks after single-dose and repetitive-dose of FFX/GnP chemotherapy. Histological examination of the primary tumors revealed that the peak period of CTC at 1–2 weeks after chemotherapy corresponded to the maximal destructive phase consisting of cell cycle arrest, apoptosis of tumor cells, and blood vessel destruction without secondary reparative tissue reactions and regeneration of tumor cells. These findings indicate that mobilization of CTCs early after chemotherapy is mediated by the shedding of degenerated tumor cells into the disrupted blood vessels driven by the pure destructive histological changes in primary tumor tissues. These results suggest that sequential CTC monitoring during chemotherapy can be a useful liquid biopsy diagnostic tool to predict tumor chemosensitivity and resistance in preclinical and clinical settings. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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11 pages, 3913 KiB  
Article
Pre-Referral Primary Care Blood Tests and Symptom Presentation before Cancer Diagnosis: National Cancer Diagnosis Audit Data
by Ben M. Cranfield, Gary A. Abel, Ruth Swann, Sarah F. Moore, Sean McPhail, Greg P. Rubin and Georgios Lyratzopoulos
Cancers 2023, 15(14), 3587; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15143587 - 12 Jul 2023
Viewed by 1371
Abstract
Background: Blood tests can support the diagnostic process in primary care. Understanding how symptomatic presentations are associated with blood test use in patients subsequently diagnosed with cancer can help to benchmark current practices and guide interventions. Methods: English National Cancer Diagnosis Audit data [...] Read more.
Background: Blood tests can support the diagnostic process in primary care. Understanding how symptomatic presentations are associated with blood test use in patients subsequently diagnosed with cancer can help to benchmark current practices and guide interventions. Methods: English National Cancer Diagnosis Audit data on 39,751 patients with incident cancer in 2018 were analysed. The frequency of four generic (full blood count, urea and electrolytes, liver function tests, and inflammatory markers) and five organ-specific (cancer biomarkers (PSA or CA125), serum protein electrophoresis, ferritin, bone profile, and amylase) blood tests was described for a total of 83 presenting symptoms. The adjusted analysis explored variation in blood test use by the symptom-positive predictive value (PPV) group. Results: There was a large variation in generic blood test use by presenting symptoms, being higher in patients subsequently diagnosed with cancer who presented with nonspecific symptoms (e.g., fatigue 81% or loss of appetite 79%), and lower in those who presented with alarm symptoms (e.g., breast lump 3% or skin lesion 1%). Serum protein electrophoresis (reflecting suspicion of multiple myeloma) was most frequently used in cancer patients who presented with back pain (18%), and amylase measurement (reflecting suspicion of pancreatic cancer) was used in those who presented with upper abdominal pain (14%). Prostate-specific antigen (PSA) use was greatest in men with cancer who presented with lower urinary tract symptoms (88%), and CA125 in women with cancer who presented with abdominal distention (53%). Symptoms with PPV values between 2.00–2.99% were associated with greater test use (64%) compared with 52% and 51% in symptoms with PPVs in the 0.01–0.99 or 1.00–1.99% range and compared with 42% and 31% in symptoms with PPVs in either the 3.00–4.99 or ≥5% range (p < 0.001). Conclusions: Generic blood test use reflects the PPV of presenting symptoms, and the use of organ-specific tests is greater in patients with symptomatic presentations with known associations with certain cancer sites. There are opportunities for greater blood test use in patients presenting with symptoms that do not meet referral thresholds (i.e., <3% PPV for cancer) where information gain to support referral decisions is likely greatest. The findings benchmark blood test use in cancer patients, highlighting opportunities for increasing use. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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13 pages, 435 KiB  
Article
The Role of Type 2 Diabetes in Patient Symptom Attribution, Help-Seeking, and Attitudes to Investigations for Colorectal Cancer Symptoms: An Online Vignette Study
by Lauren Smith, Christian Von Wagner, Aradhna Kaushal, Meena Rafiq, Georgios Lyratzopoulos and Cristina Renzi
Cancers 2023, 15(6), 1668; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15061668 - 08 Mar 2023
Viewed by 1439
Abstract
Objectives: Type 2 diabetes is associated with a higher risk of colorectal cancer (CRC) and advanced-stage cancer diagnosis. To help diagnose cancer earlier, this study aimed at examining whether diabetes might influence patient symptom attribution, help-seeking, and willingness to undergo investigations for possible [...] Read more.
Objectives: Type 2 diabetes is associated with a higher risk of colorectal cancer (CRC) and advanced-stage cancer diagnosis. To help diagnose cancer earlier, this study aimed at examining whether diabetes might influence patient symptom attribution, help-seeking, and willingness to undergo investigations for possible CRC symptoms. Methods: A total of 1307 adults (340 with and 967 without diabetes) completed an online vignette survey. Participants were presented with vignettes describing new-onset red-flag CRC symptoms (rectal bleeding or a change in bowel habits), with or without additional symptoms of diabetic neuropathy. Following the vignettes, participants were asked questions on symptom attribution, intended help-seeking, and attitudes to investigations. Results: Diabetes was associated with greater than two-fold higher odds of attributing changes in bowel habits to medications (OR = 2.48; 95% Cl 1.32–4.66) and of prioritising diabetes-related symptoms over the change in bowel habits during medical encounters. Cancer was rarely mentioned as a possible explanation for the change in bowel habits, especially among diabetic participants (10% among diabetics versus 16% in nondiabetics; OR = 0.55; 95% CI 0.36–0.85). Among patients with diabetes, those not attending annual check-ups were less likely to seek help for red-flag cancer symptoms (OR = 0.23; 95% Cl 0.10–0.50). Conclusions: Awareness of possible cancer symptoms was low overall. Patients with diabetes could benefit from targeted awareness campaigns emphasising the importance of discussing new symptoms such as changes in bowel habits with their doctor. Specific attention is warranted for individuals not regularly attending healthcare despite their chronic morbidity. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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12 pages, 692 KiB  
Article
Impact of the COVID-19 Outbreak—Delayed Referral of Colorectal and Lung Cancer in Primary Care: A National Retrospective Cohort Study
by Charles W. Helsper, Carla H. Van Gils, Nicole F. Van Erp, Marinde F. R. Siepman van den Berg, Omar Rogouti, Kristel M. Van Asselt, Otto R. Maarsingh, Jean Muris, Daan Brandenbarg, Sabine Siesling, Niek J. De Wit, Matthew P. Grant and on behalf of the COVID and Cancer Consortium
Cancers 2023, 15(5), 1462; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15051462 - 25 Feb 2023
Cited by 1 | Viewed by 1392
Abstract
The Coronavirus disease 2019 (COVID-19) outbreak impacted health care. We investigated its impact on the time to referral and diagnosis for symptomatic cancer patients in The Netherlands. We performed a national retrospective cohort study utilizing primary care records linked to The Netherlands Cancer [...] Read more.
The Coronavirus disease 2019 (COVID-19) outbreak impacted health care. We investigated its impact on the time to referral and diagnosis for symptomatic cancer patients in The Netherlands. We performed a national retrospective cohort study utilizing primary care records linked to The Netherlands Cancer Registry. For patients with symptomatic colorectal, lung, breast, or melanoma cancer, we manually explored free and coded texts to determine the durations of the primary care (IPC) and secondary care (ISC) diagnostic intervals during the first COVID-19 wave and pre-COVID-19. We found that the median IPC duration increased for colorectal cancer from 5 days (Interquartile Range (IQR) 1–29 days) pre-COVID-19 to 44 days (IQR 6–230, p < 0.01) during the first COVID-19 wave, and for lung cancer, the duration increased from 15 days (IQR) 3–47) to 41 days (IQR 7–102, p < 0.01). For breast cancer and melanoma, the change in IPC duration was negligible. The median ISC duration only increased for breast cancer, from 3 (IQR 2–7) to 6 days (IQR 3–9, p < 0.01). For colorectal cancer, lung cancer, and melanoma, the median ISC durations were 17.5 (IQR (9–52), 18 (IQR 7–40), and 9 (IQR 3–44) days, respectively, similar to pre-COVID-19 results. In conclusion, for colorectal and lung cancer, the time to primary care referral was substantially prolonged during the first COVID-19 wave. In such crises, targeted primary care support is needed to maintain effective cancer diagnosis. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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13 pages, 1246 KiB  
Article
Urine CA125 and HE4 for the Detection of Ovarian Cancer in Symptomatic Women
by Chloe E. Barr, Kelechi Njoku, Gemma L. Owens and Emma J. Crosbie
Cancers 2023, 15(4), 1256; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15041256 - 16 Feb 2023
Cited by 2 | Viewed by 1873
Abstract
The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in [...] Read more.
The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in symptomatic women. Paired urine and serum samples were collected from women undergoing treatment for ovarian cancer (cases) or investigations for gynaecological symptoms (controls). Biomarkers were measured using an automated chemiluminescent enzyme immunoassay analyser. Standard diagnostic accuracy metrics were calculated. In total, 114 women were included, of whom 17 (15%) were diagnosed with an epithelial ovarian malignancy. Levels of urine CA125 and HE4 were significantly elevated in women with ovarian cancer compared to controls [CA125: 8.5 U/mL (IQR: 2.4–19.5) vs. 2.3 U/mL (IQR: 1.0–6.4), p = 0.01. HE4: 12.0 nmol/L (IQR: 10.3–23.1) vs. 6.7 nmol/L (IQR: 3.4–13.6), p = 0.006]. Urine CA125 and HE4 detected ovarian cancer with an AUC of 0.69 (95% CI: 0.55–0.82) and 0.71 (95% CI: 0.69–0.82), respectively (p = 0.73). A combination of urine CA125 and HE4 at optimal thresholds had a sensitivity of 82.4% (95% CI: 56.6–96.2) and was comparable to the sensitivity of serum CA125 [88.2% (95% CI: 63.6–98.5)]. Larger studies are required to confirm our findings, standardise urine collection, and evaluate optimal biomarker thresholds. Urine CA125 and HE4 may be useful non-invasive diagnostic tools to triage women for formal ovarian cancer investigations. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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14 pages, 1077 KiB  
Article
Development and Internal Validation of a Risk Prediction Model to Identify Myeloma Based on Routine Blood Tests: A Case-Control Study
by Lesley Smith, Jonathan Carmichael, Gordon Cook, Bethany Shinkins and Richard D. Neal
Cancers 2023, 15(3), 975; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15030975 - 03 Feb 2023
Cited by 1 | Viewed by 1775
Abstract
Myeloma is one of the hardest cancers to diagnose in primary care due to its rarity and non-specific symptoms. A rate-limiting step in diagnosing myeloma is the clinician considering myeloma and initiating appropriate investigations. We developed and internally validated a risk prediction model [...] Read more.
Myeloma is one of the hardest cancers to diagnose in primary care due to its rarity and non-specific symptoms. A rate-limiting step in diagnosing myeloma is the clinician considering myeloma and initiating appropriate investigations. We developed and internally validated a risk prediction model to identify those with a high risk of having undiagnosed myeloma based on results from routine blood tests taken for other reasons. A case-control study, based on 367 myeloma cases and 1488 age- and sex-matched controls, was used to develop a risk prediction model including results from 15 blood tests. The model had excellent discrimination (C-statistic 0.85 (95%CI 0.83, 0.89)) and good calibration (calibration slope 0.87 (95%CI 0.75, 0.90)). At a prevalence of 15 per 100,000 population and a probability threshold of 0.4, approximately 600 patients would need additional reflex testing to detect one case. We showed that it is possible to combine signals and abnormalities from several routine blood test parameters to identify individuals at high-risk of having undiagnosed myeloma who may benefit from additional reflex testing. Further work is needed to explore the full potential of such a strategy, including whether it is clinically useful and cost-effective and how to make it ethically acceptable. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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35 pages, 1923 KiB  
Article
Diagnostic Performance of Biomarkers for Bladder Cancer Detection Suitable for Community and Primary Care Settings: A Systematic Review and Meta-Analysis
by Evie Papavasiliou, Valerie A. Sills, Natalia Calanzani, Hannah Harrison, Claudia Snudden, Erica di Martino, Andy Cowan, Dawnya Behiyat, Rachel Boscott, Sapphire Tan, Jennifer Bovaird, Grant D. Stewart, Fiona M. Walter and Yin Zhou
Cancers 2023, 15(3), 709; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15030709 - 24 Jan 2023
Cited by 1 | Viewed by 2140
Abstract
Evidence on the use of biomarkers to detect bladder cancer in the general population is scarce. This study aimed to systematically review evidence on the diagnostic performance of biomarkers which might be suitable for use in community and primary care settings [PROSPERO Registration: [...] Read more.
Evidence on the use of biomarkers to detect bladder cancer in the general population is scarce. This study aimed to systematically review evidence on the diagnostic performance of biomarkers which might be suitable for use in community and primary care settings [PROSPERO Registration: CRD42021258754]. Database searches on MEDLINE and EMBASE from January 2000 to May 2022 resulted in 4914 unique citations, 44 of which met inclusion criteria. Included studies reported on 112 biomarkers and combinations. Heterogeneity of designs, populations and outcomes allowed for the meta-analysis of three biomarkers identified in at least five studies (NMP-22, UroVysion, uCyt+). These three biomarkers showed similar discriminative ability (adjusted AUC estimates ranging from 0.650 to 0.707), although for NMP-22 and UroVysion there was significant unexplained heterogeneity between included studies. Narrative synthesis revealed the potential of these biomarkers for use in the general population based on their reported clinical utility, including effects on clinicians, patients, and the healthcare system. Finally, we identified some promising novel biomarkers and biomarker combinations (N < 3 studies for each biomarker/combination) with negative predictive values of ≥90%. These biomarkers have potential for use as a triage tool in community and primary care settings for reducing unnecessary specialist referrals. Despite promising emerging evidence, further validation studies in the general population are required at different stages within the diagnostic pathway. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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19 pages, 898 KiB  
Article
Factors Associated with the Breast Cancer Diagnostic Interval across Five Canadian Provinces: A CanIMPACT Retrospective Cohort Study
by Arlinda Ruco, Patti A. Groome, Mary L. McBride, Kathleen M. Decker, Eva Grunfeld, Li Jiang, Cynthia Kendell, Aisha Lofters, Robin Urquhart, Khanh Vu and Marcy Winget
Cancers 2023, 15(2), 404; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15020404 - 07 Jan 2023
Cited by 1 | Viewed by 1515
Abstract
The cancer diagnostic process can be protracted, and it is a time of great anxiety for patients. The objective of this study was to examine inter- and intra-provincial variation in diagnostic intervals and explore factors related to the variation. This was a multi-province [...] Read more.
The cancer diagnostic process can be protracted, and it is a time of great anxiety for patients. The objective of this study was to examine inter- and intra-provincial variation in diagnostic intervals and explore factors related to the variation. This was a multi-province retrospective cohort study using linked administrative health databases. All females with a diagnosis of histologically confirmed invasive breast cancer in British Columbia (2007–2010), Manitoba (2007–2011), Ontario (2007–2010), Nova Scotia (2007–2012), and Alberta (2004–2010) were included. The start of the diagnostic interval was determined using algorithms specific to whether the patient’s cancer was detected through screening. We used multivariable quantile regression analyses to assess the association between demographic, clinical and healthcare utilization factors with the diagnostic interval outcome. We found significant inter- and intra-provincial variation in the breast cancer diagnostic interval and by screen-detection status; patients who presented symptomatically had longer intervals than screen-detected patients. Interprovincial diagnostic interval variation was 17 and 16 days for screen- and symptom-detected patients, respectively, at the median, and 14 and 41 days, respectively, at the 90th percentile. There was an association of longer diagnostic intervals with increasing comorbid disease in all provinces in non-screen-detected patients but not screen-detected. Longer intervals were observed across most provinces in screen-detected patients living in rural areas. Having a regular primary care provider was not associated with a shorter diagnostic interval. Our results highlight important findings regarding the length of the breast cancer diagnostic interval, its variation within and across provinces, and its association with comorbid disease and rurality. We conclude that diagnostic processes can be context specific, and more attention should be paid to developing tailored processes so that equitable access to a timely diagnosis can be achieved. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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12 pages, 261 KiB  
Article
Barriers to Early Presentation amongst Rural Residents Experiencing Symptoms of Colorectal Cancer: A Qualitative Interview Study
by Christina Dobson, Jennifer Deane, Sara Macdonald, Peter Murchie, Christina Ellwood, Lorraine Angell and Greg Rubin
Cancers 2023, 15(1), 274; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15010274 - 31 Dec 2022
Cited by 1 | Viewed by 1603
Abstract
Rural cancer inequalities are evident internationally, with rural cancer patients 5% less likely to survive than their urban counterparts. There is evidence to suggest that diagnostic delays prior to entry into secondary care may be contributing to these poorer rural cancer outcomes. This [...] Read more.
Rural cancer inequalities are evident internationally, with rural cancer patients 5% less likely to survive than their urban counterparts. There is evidence to suggest that diagnostic delays prior to entry into secondary care may be contributing to these poorer rural cancer outcomes. This study explores the symptom appraisal and help-seeking decision-making of people experiencing symptoms of colorectal cancer in rural areas of England. Patients were randomly invited from 4 rural practices, serving diverse communities. Semi-structured interviews were undertaken with 40 people who had experienced symptoms of colorectal cancer in the preceding 8 weeks. Four key themes were identified as influential in participants’ willingness and timeliness of consultation: a desire to rule out cancer (facilitator of help-seeking); stoicism and self-reliance (barrier to help-seeking); time scarcity (barrier to help-seeking); and GP/patient relationship (barrier or facilitator, depending on perceived strength of the relationship). Self-employed, and “native” rural residents most commonly reported experiencing time scarcity and poor GP/patient relationships as a barrier to (re-)consultation. Targeted, active safety-netting approaches, and increased continuity of care, may be particularly beneficial to expedite timely diagnoses and minimise cancer inequalities for rural populations. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
18 pages, 1607 KiB  
Article
How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States
by Monica Zigman Suchsland, Lesleigh Kowalski, Hannah A. Burkhardt, Maria G. Prado, Larry G. Kessler, Meliha Yetisgen, Maggie A. Au, Kari A. Stephens, Farhood Farjah, Anneliese M. Schleyer, Fiona M. Walter, Richard D. Neal, Kevin Lybarger, Caroline A. Thompson, Morhaf Al Achkar, Elizabeth A. Sarma, Grace Turner and Matthew Thompson
Cancers 2022, 14(23), 5756; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14235756 - 23 Nov 2022
Cited by 4 | Viewed by 1859
Abstract
The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time [...] Read more.
The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012–2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273–691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11–240), specialist consultation to diagnosis 72 days (IQR 13–456), and from diagnosis to treatment initiation 7 days (IQR 0–36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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14 pages, 926 KiB  
Article
The Effect of Older Age and Frailty on the Time to Diagnosis of Cancer: A Connected Bradford Electronic Health Records Study
by Charlotte Summerfield, Lesley Smith, Oliver Todd, Cristina Renzi, Georgios Lyratzopoulos, Richard D. Neal and Daniel Jones
Cancers 2022, 14(22), 5666; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14225666 - 18 Nov 2022
Cited by 2 | Viewed by 1678
Abstract
Over 60% of cancer diagnoses in the UK are in patients aged 65 and over. Cancer diagnosis and treatment in older adults is complicated by the presence of frailty, which is associated with lower survival rates and poorer quality of life. This population-based [...] Read more.
Over 60% of cancer diagnoses in the UK are in patients aged 65 and over. Cancer diagnosis and treatment in older adults is complicated by the presence of frailty, which is associated with lower survival rates and poorer quality of life. This population-based cohort study used a longitudinal database to calculate the time between presentation to primary care with a symptom suspicious of cancer and a confirmed cancer diagnosis for 7460 patients in the Bradford District. Individual frailty scores were calculated using the electronic frailty index (eFI) and categorised by severity. The median time from symptomatic presentation to cancer diagnosis for all patients was 48 days (IQR 21–142). 23% of the cohort had some degree of frailty. After adjustment for potential confounders, mild frailty added 7 days (95% CI 3–11), moderate frailty 23 days (95% CI 4–42) and severe frailty 11 days (95% CI −27–48) to the median time to diagnosis compared to not frail patients. Our findings support use of the eFI in primary care to identify and address patient, healthcare and system factors that may contribute to diagnostic delay. We recommend further research to explore patient and clinician factors when investigating cancer in frail patients. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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12 pages, 852 KiB  
Article
The Impact of the COVID Pandemic on the Incidence of Presentations with Cancer-Related Symptoms in Primary Care
by Matthew P. Grant, Charles W. Helsper, Rebecca Stellato, Nicole van Erp, Kristel M. van Asselt, Pauline Slottje, Jean Muris, Daan Brandenbarg, Niek J. de Wit and Carla H. van Gils
Cancers 2022, 14(21), 5353; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14215353 - 30 Oct 2022
Cited by 5 | Viewed by 1551
Abstract
Introduction: In the Netherlands, the onset of the coronavirus pandemic saw shifts in primary health service provision away from physical consultations, cancer-screening programs were temporarily halted, and government messaging focused on remaining at home. In March and April 2020, weekly cancer diagnoses decreased [...] Read more.
Introduction: In the Netherlands, the onset of the coronavirus pandemic saw shifts in primary health service provision away from physical consultations, cancer-screening programs were temporarily halted, and government messaging focused on remaining at home. In March and April 2020, weekly cancer diagnoses decreased to 73% of their pre-COVID levels, and 39% for skin cancer. This study aims to explore the effect of the COVID pandemic on patient presentations for cancer-related symptoms in primary care in The Netherlands. Methods: Retrospective cohort study using routine clinical primary care data. Monthly incidences of patient presentations for cancer-related symptoms in five clinical databases in The Netherlands were analysed from March 2018 to February 2021. Results: Data demonstrated reductions in the incidence of cancer-related symptom presentations to primary care during the first COVID wave (March-June 2020) of −34% (95% CI: −43 to −23%) for all symptoms combined. In the second wave (October 2020–February 2021) there was no change in incidence observed (−8%, 95% CI −20% to 6%). Alarm-symptoms demonstrated decreases in incidence in the first wave with subsequent incidences that continued to rise in the second wave, such as: first wave: breast lump −17% (95% CI: −27 to −6%) and haematuria −15% (95% CI −24% to −6%); and second wave: rectal bleeding +14% (95% CI: 0 to 30%) and breast lump +14% (95% CI: 2 to 27%). Presentations of common non-alarm symptom such as tiredness and naevus demonstrated decreased in-cidences in the first wave of 45% (95% CI: −55% to −33%) and 37% (95% CI −47% to −25%). In the second wave, tiredness incidence was reduced by 20% (95% CI: −33% to −3%). Subgroup analy-sis did not demonstrate difference in incidence according to sex, age groups, comorbidity status, or previous history of cancer. Conclusions: These data describe large-scale primary care avoidance that did not increase until the end of the first COVID year for many cancer-related symptoms, suggestive that substantial numbers of patients delayed presenting to primary care. For those patients who had underlying cancer, this may have had impacted the cancer stage at diagnosis, treatment, and mortality. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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13 pages, 599 KiB  
Article
Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools
by Emma Briggs, Marc de Kamps, Willie Hamilton, Owen Johnson, Ciarán D. McInerney and Richard D. Neal
Cancers 2022, 14(20), 5023; https://doi.org/10.3390/cancers14205023 - 14 Oct 2022
Cited by 6 | Viewed by 2044
Abstract
Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of [...] Read more.
Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electronic health record. We used a primary care electronic health record dataset derived from the UK General Practice Research Database (7471 cases; 32,877 controls) and developed five probabilistic machine learning classifiers: Support Vector Machine, Random Forest, Logistic Regression, Naïve Bayes, and Extreme Gradient Boosted Decision Trees. Features included basic demographics, symptoms, and lab test results. The Logistic Regression, Support Vector Machine, and Extreme Gradient Boosted Decision Tree models achieved the highest performance in terms of accuracy and AUROC (0.89 accuracy, 0.87 AUROC), outperforming a current UK oesophago-gastric cancer risk-assessment tool (ogRAT). Machine learning also identified more cancer patients than the ogRAT: 11.0% more with little to no effect on false positives, or up to 25.0% more with a slight increase in false positives (for Logistic Regression, results threshold-dependent). Feature contribution estimates and individual prediction explanations indicated clinical relevance. We conclude that machine learning could improve primary care cancer risk-assessment tools, potentially helping clinicians to identify additional cancer cases earlier. This could, in turn, improve survival outcomes. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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16 pages, 1829 KiB  
Article
Urine CA125 and HE4 for the Triage of Symptomatic Women with Suspected Endometrial Cancer
by Kelechi Njoku, Chloe E. Barr, Caroline J. J. Sutton and Emma J. Crosbie
Cancers 2022, 14(14), 3306; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14143306 - 06 Jul 2022
Cited by 8 | Viewed by 3332
Abstract
A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic [...] Read more.
A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic women. This was a cross-sectional diagnostic accuracy study of 153 symptomatic women who underwent urgent diagnostic investigations for suspected endometrial cancer at a large gynecological cancer center. Urine samples were collected prior to routine clinical procedures. Urine CA125 and HE4 levels were determined using automated chemiluminescent enzyme immunoassays. Univariate and multivariable receiver operating characteristic (ROC) curve analyses were performed. Urine CA125 and HE4 were discovered to be significantly elevated in women with endometrial cancer, compared to controls (p < 0.001 and p = 0.01, respectively). Urine CA125 and HE4 detected endometrial cancer with an area under the ROC curve (AUC) of 0.89 (0.81, 0.98) and 0.69 (0.55, 0.83), respectively. CA125 exhibited good discriminatory potential for Type I and early-stage tumors (AUC 0.93 and 0.90, respectively). A diagnostic model that combined urine CA125 and transvaginal ultrasound-measured endometrial thickness predicted endometrial cancer with an AUC of 0.96 (0.91, 1.00). Urine CA125 displays potential as a diagnostic tool for symptomatic women with suspected endometrial cancer. When combined with transvaginal ultrasound-measured endometrial thickness, this patient-friendly, urine-based test could help triage women for invasive diagnostics or safe reassurance, reducing costs and improving patient experience. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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18 pages, 2141 KiB  
Article
The Performance of HE4 Alone and in Combination with CA125 for the Detection of Ovarian Cancer in an Enriched Primary Care Population
by Chloe E. Barr, Garth Funston, David Jeevan, Sudha Sundar, Luke T. A. Mounce and Emma J. Crosbie
Cancers 2022, 14(9), 2124; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14092124 - 24 Apr 2022
Cited by 14 | Viewed by 4680
Abstract
Human epididymis 4 (HE4) is a promising ovarian cancer biomarker, but it has not been evaluated in primary care. In this prospective observational study, we investigated the diagnostic accuracy of HE4 alone and in combination with CA125 for the detection of ovarian cancer [...] Read more.
Human epididymis 4 (HE4) is a promising ovarian cancer biomarker, but it has not been evaluated in primary care. In this prospective observational study, we investigated the diagnostic accuracy of HE4 alone and in combination with CA125 for the detection of ovarian cancer in symptomatic women attending primary care. General practitioner (GP)-requested CA125 samples were tested for HE4 at a large teaching hospital in Manchester, and cancer outcomes were tracked for 12 months. We found a low incidence of ovarian cancer in primary care; thus, the cohort was enriched with pre-surgical samples from 81 ovarian cancer patients. The Risk of Ovarian Malignancy Algorithm (ROMA) was calculated using age (</>51) as a surrogate for menopause. Conventional diagnostic accuracy metrics were determined. A total of 1229 patients were included; 82 had ovarian cancer. Overall, ROMA performed best (AUC-0.96 (95%CI: 0.94–0.98, p = <0.001)). In women under 50 years, the combination of CA125 and HE4 (either marker positive) was superior (sensitivity: 100% (95%CI: 81.5–100.0), specificity: 80.1% (95%CI 76.7–83.1)). In women over 50, ROMA performed best (sensitivity: 84.4% (95%CI: 73.1–92.2), specificity: 87.2% (95%CI 84.1–90)). HE4 and ROMA may improve ovarian cancer detection in primary care, particularly for women under 50 years, in whom diagnosis is challenging. Validation in a larger primary care cohort is required. Full article
(This article belongs to the Special Issue Cancer Detection in Primary Care)
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