Is symptom-based diagnosis of lung cancer possible? A systematic review and meta-analysis of symptomatic lung cancer prior to diagnosis for comparison with real-time data from routine general practice

SMARCA4-deficient non-small cell lung cancer with metastasis to the sigmoid colon: a case report

BACKGROUND

SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4-deficient non-small cell lung cancer (SMARCA4-dNSCLC) is a rare subtype of NSCLC whose definitive radiographic characteristics have not yet been fully delineated. Clinically, these tumors often metastasize to distant organs and lymph nodes at an early stage, which is strongly associated with poor clinical prognosis. The common metastatic sites include bone, brain, adrenal glands, liver, and spleen, whereas intestinal metastasis is extremely rare. In this case, we describe a rare instance of SMARCA4-deficient NSCLC with metastasis to the sigmoid colon.

CASE DESCRIPTION

A 59-year-old male presented with hoarseness and shortness of breath. Computed tomography (CT) imaging revealed an irregular mass in the posterior apical segment of the upper lobe of the left lung, with enlarged lymph nodes in the mediastinum and left lung hilum. A biopsy of the lung mass confirmed the diagnosis of NSCLC with SMARCA4 gene deletion. CT also revealed uneven thickening of the sigmoid colon wall, which was proved to be metastases from the lung cancer through surgical pathology. The patient initially underwent chemotherapy combined with immunotherapy and intensity-modulated radiotherapy for the lungs. However, a follow-up CT revealed progression in the sigmoid colon tumor. Consequently, the patient underwent laparoscopic radical sigmoid colectomy with regional lymph node dissection. Two months postoperatively, metastasis to the left adrenal gland was detected. The treatment regimen was adjusted to a combination therapy consisting of gemcitabine, nedaplatin, bevacizumab, and camrelizumab accordingly. The patient demonstrated a favorable response to this treatment, with no evidence of recurrence or further metastasis to date.

CONCLUSIONS

This case represents the first reported instance of SMARCA4-dNSCLC with metastasis to the sigmoid colon. The atypical clinical and radiological features of this condition pose significant diagnostic challenges, particularly in differentiating metastatic lesions from primary colonic tumors. This case underscores the significance of recognizing rare metastatic patterns in SMARCA4-dNSCLC, enriching the literature on its diverse manifestations and providing a critical reference for clinicians in diagnosing and managing SMARCA4-dNSCLC with sigmoid colon metastasis.

Are we ready? assessing effectiveness and implementation of cancer control strategies in primary care: a comprehensive review of systematic reviews

BACKGROUND

Cancer is a major global cause of death, and primary care is crucial for cancer prevention and early detection. However, there is conflicting information on the effectiveness, implementation, and sustainability of cancer control interventions in primary care.

OBJECTIVE

This study aimed to summarize the evidence for cancer control in primary care, focussing on identifying relevant factors for implementation and sustainability.

STUDY SETTING AND DESIGN

We conducted a narrative, mixed-methods review of systematic reviews, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Four databases were screened, and two independent reviewers selected studies reporting on cancer prevention, screening, or early detection in primary or community settings. We analysed findings using the extended Reach-Effectiveness-Adopt-Implementation-Maintenance (RE-AIM) Framework.

PRINCIPAL FINDINGS

From the 37 reviews that met the inclusion criteria, 6 focussed on primary prevention, 23 on screening, and 12 on early detection. Most reviews (78%) addressed intervention effectiveness, such as HPV vaccination, tobacco cessation, and cervical, breast, and colorectal screening. One-third of the reviews mentioned adoption and implementation factors, including barriers and facilitators to the implementation of cancer screening programs. Only one review addressed maintenance and sustainability factors, exploring continuous resources and funding strategies.

CONCLUSION

While numerous interventions are effective for cancer prevention and detection in primary care, literature on implementation and sustainability strategies is lacking. Focusing on continuous resources and funding for cancer strategies in primary care may aid sustainability. Future research should prioritize reporting on implementation and sustainability factors to enhance cancer prevention and control in primary care settings.

Smoking status, symptom significance and healthcare seeking with lung cancer symptoms in the Danish general population

This study analyses the associations between smoking status and perceived symptom significance (concern and influence on daily activity) among individuals with possible lung cancer symptoms and investigate the influence of symptom significance on healthcare seeking among individuals with different smoking status. A nationwide survey with 21,920 randomly selected individuals aged ≥40 years included questions about lung cancer symptoms, symptom concern and influence on daily activities, GP contact, and smoking status. Descriptive statistics and multivariable regression models were applied. Overall, individuals who currently smoked were more likely to perceive their lung cancer symptoms as significant, and individuals who reported high symptom significance were more likely to seek healthcare with both specific and non-specific symptoms. The significance of symptoms appeared to have less pronounced effect on prompting healthcare seeking among individuals with a history of current smoking. This implies that they may benefit from support and encouragement to seek care.

Transformer-based deep learning model for the diagnosis of suspected lung cancer in primary care based on electronic health record data

BACKGROUND

Due to its late stage of diagnosis lung cancer is the commonest cause of death from cancer in the UK. Existing epidemiological risk models in clinical usage, which have Positive Predictive Values (PPV) of less than 10%, do not consider the temporal relations expressed in sequential electronic health record (EHR) data. We aimed to build a model for lung cancer early detection in primary care using machine learning with deep 'transformer' models on EHR data to learn from these complex sequential 'care pathways'.

METHODS

We split the Whole Systems Integrated Care (WSIC) dataset into 70% training and 30% validation. Within the training set we created a case-control study with lung cancer cases and control cases of 'other' cancers or respiratory conditions or 'other' non cancer conditions. Based on 3,303,992 patients from January 1981 to December 2020 there were 11,847 lung cancer cases. 5789 cases and 7240 controls were used for training and 50,000 randomly selected patients out of the whole validation population of 368,906 for validation. GP EHR data going back three years from the date of diagnosis less the most recent one months were semantically pre-processed by mapping from more than 30,000 terms to 450. Model building was performed using ALBERT with a Logistic Regression Classifier (LRC) head. Clustering was explored using k-means. An additional regression model alone was built on the pre-processed data as a comparator.

FINDINGS

Our model achieved an AUROC of 0.924 (95% CI 0.921-0.927) with a PPV of 3.6% (95% CI 3.5-3.7) and Sensitivity of 86.6% (95% CI 85.3-87.8) based on the three year's data prior to diagnosis less the immediate month before index diagnosis. The comparator regression model achieved a PPV of 3.1% (95% CI 3.0-3.1) and AUROC of 0.887 (95% CI 0.884-0.889). We interpreted our model using cluster analysis and have identified six groups of patients exhibiting similar lung cancer progression patterns and clinical investigation patterns.

INTERPRETATION

Capturing temporal sequencing between cancer and non-cancer pathways to diagnosis enables much more accurate models. Future work will focus on external dataset validation and integration into GP clinical systems for evaluation.

FUNDING

Cancer Research UK.

Development of a predictive score to discriminate community acquired pneumonia with underlying lung cancer: A retrospective case - control study

BACKGROUND

A pneumonic infiltrate might hide an occult lung cancer (LC). This awareness depends on each clinician personal experience, turning definitive LC diagnosis challenging and possibly delayed. In this study we aimed to develop a clinical score to better identify those cases.

MATERIALS AND METHODS

We conducted a retrospective case-control study, including previously undiagnosed LC patients admitted in our institution, with a presumptive suspicious of community acquired pneumonia (CAP). Cases were compared with random CAP inpatient controls, using a matched 2:1 ratio. Demographic, clinical, and laboratorial variables were assessed for a possible association with the presence of a CAP with underlying LC (CAP-uLC).

RESULTS

Among 535 hospitalized LC patients, 43 cases had a presentation compatible with CAP and were compared with 86 CAP controls. A scoring system was built using 6 independent variables, which positively correlated with CAP-uLC: smoking history (OR: 8.3 [1.9-36.2]; p = 0.005); absence of fever (6.5 [2.0-21.5]; p = 0.002); sputum with blood (5.9 [1.2-29.9]; p = 0.033); platelet count ≥ 232x103/μL (5.8 [1.6-20.6]; p = 0.006); putative alternative diagnosis than CAP (4.6 [1.5-14.7]; p = 0.009); and duration of symptoms ≥ 10 days (3.7 [1.1-13.0]; p = 0.037). Our score presented an AUC of 0.910 (95 % CI, 0.852-0.967; p < 0.001), a sensitivity of 88.1 % and specificity of 84.7 %, in predicting the risk of presenting a CAP-uLC, when set to a cutoff of 18.

CONCLUSION

We propose a novel risk score aimed to aid clinicians identifying patients with CAP-uLC in the acute setting, possibly prompting early LC diagnosis.

The journey of lung cancer patients from symptoms to diagnosis in Greece. A mixed methods approach

The early diagnosis of lung cancer improves the probability of successful treatment. However, patients and physicians face several difficulties that can considerably delay the diagnostic process. A mixed-methods study that would follow the patient's journey throughout the diagnostic process could alleviate these difficulties. This study aimed to (a) track the patients' journey from the onset of symptoms until diagnosis and, (b) explore the patients' perspective of the journey until diagnosis, on the largest island of Greece. A convergent mixed-methods study was conducted with 94 patients with lung cancer. Patients completed a self-report questionnaire and were interviewed about their symptoms and journey through the healthcare system before their diagnosis. Our findings revealed several problems and delays in the diagnostic process. Both quantitative and qualitative data showed that patients did not recognize their symptoms and sought medical advice in time because they overlooked or attributed their symptoms to 'simpler'/'more common' causes. Furthermore, most patients were diagnosed 1-3 months after their first visit to a physician for their symptoms. Qualitative data analysis revealed three broad categories of problems that delayed diagnosis: (1) physician missteps, (2) administrative problems, and (3) the effect of the Covid-19 pandemic. This study found that major issues and delays prolong the diagnostic process for lung cancer. Therefore, optimization of diagnostic processes at each level of healthcare and interspecialty cooperation programs are needed. Furthermore, population-based interventions and patient education can help lung cancer patients be diagnosed early and improve their quality of life and disease outcomes.

Guideline concordance for timely chest imaging after new presentations of dyspnoea or haemoptysis in primary care: a retrospective cohort study

BACKGROUND

Guidelines recommend urgent chest X-ray for newly presenting dyspnoea or haemoptysis but there is little evidence about their implementation.

METHODS

We analysed linked primary care and hospital imaging data for patients aged 30+ years newly presenting with dyspnoea or haemoptysis in primary care during April 2012 to March 2017. We examined guideline-concordant management, defined as General Practitioner-ordered chest X-ray/CT carried out within 2 weeks of symptomatic presentation, and variation by sociodemographic characteristic and relevant medical history using logistic regression. Additionally, among patients diagnosed with cancer we described time to diagnosis, diagnostic route and stage at diagnosis by guideline-concordant status.

RESULTS

In total, 22 560/162 161 (13.9%) patients with dyspnoea and 4022/8120 (49.5%) patients with haemoptysis received guideline-concordant imaging within the recommended 2-week period. Patients with recent chest imaging pre-presentation were much less likely to receive imaging (adjusted OR 0.16, 95% CI 0.14-0.18 for dyspnoea, and adjusted OR 0.09, 95% CI 0.06-0.11 for haemoptysis). History of chronic obstructive pulmonary disease/asthma was also associated with lower odds of guideline concordance (dyspnoea: OR 0.234, 95% CI 0.225-0.242 and haemoptysis: 0.88, 0.79-0.97). Guideline-concordant imaging was lower among dyspnoea presenters with prior heart failure; current or ex-smokers; and those in more socioeconomically disadvantaged groups.The likelihood of lung cancer diagnosis within 12 months was greater among the guideline-concordant imaging group (dyspnoea: 1.1% vs 0.6%; haemoptysis: 3.5% vs 2.7%).

CONCLUSION

The likelihood of receiving urgent imaging concords with the risk of subsequent cancer diagnosis. Nevertheless, large proportions of dyspnoea and haemoptysis presenters do not receive prompt chest imaging despite being eligible, indicating opportunities for earlier lung cancer diagnosis.

A population-based study on social inequality and barriers to healthcare-seeking with lung cancer symptoms

Healthcare-seeking with lung cancer symptoms is a prerequisite for improving timely diagnosis of lung cancer. In this study we aimed to explore barriers towards contacting the general practitioner (GP) with lung cancer symptoms, and to analyse the impact of social inequality. The study is based on a nationwide survey with 69,060 individuals aged ≥40 years, randomly selected from the Danish population. The survey included information on lung cancer symptoms, GP contacts, barriers to healthcare-seeking and smoking status. Information about socioeconomics was obtained by linkage to Danish Registers. Descriptive statistics and multivariate logistic regression model were used to analyse the data. “Being too busy” and “Being worried about wasting the doctor’s time” were the most frequent barriers to healthcare-seeking with lung cancer symptoms. Individuals out of workforce and individuals who smoked more often reported “Being worried about what the doctor might find” and “Being too embarrassed” about the symptoms. The social inequality in barriers to healthcare-seeking with lung cancer symptoms is noticeable, which emphasises the necessity of focus on vulnerable groups at risk of postponing relevant healthcare-seeking.

A systematic review of interventions to recognise, refer and diagnose patients with lung cancer symptoms

Patients with lung cancer (LC) often experience delay between symptom onset and treatment. Primary healthcare professionals (HCPs) can help facilitate early diagnosis of LC through recognising early signs and symptoms and making appropriate referrals. This systematic review describes the effect of interventions aimed at helping HCPs recognise and refer individuals with symptoms suggestive of LC. Seven studies were synthesised narratively. Outcomes were categorised into: Diagnostic intervals; referral and diagnosis patterns; stage distribution at diagnosis; and time interval from diagnosis to treatment. Rapid access pathways and continuing medical education for general practitioners can help reduce LC diagnostic and treatment delay. Awareness campaigns and HCP education can help inform primary HCPs about referral pathways. However, campaigns did not significantly impact LC referral rates or reduce diagnostic intervals. Disease outcomes, such as LC stage at diagnosis, recurrence, and survival were seldom measured. Review findings highlight the need for longitudinal, powered, and controlled studies.

[Delay in the diagnosis and treatment of five types of cancer in two urban health centres]

OBJECTIVES

To assess the diagnostic (ID) and treatment (IT) intervals of the most prevalent cancers in patients attached to two health centres and to analyse the influence of sociodemographic, clinical and health system (HS) organisational factors.

DESIGN

Observational, retrospective, analytical cohort study. SITE: Primary care. Two urban health centres.

PARTICIPANTS

Three hundred sixty-five patients diagnosed with colorectal cancer (CRC), breast, lung, prostate or bladder cancer between 1/1/2012 and 31/12/2017.

MAIN MEASURES

The medians of ID and IT and the risk (OR) of ID and IT above those medians according to the above factors are compared. The contribution of each process step to ID is analysed.

RESULTS

Median ID was 92 days, maximum in prostate cancer (395 days) and minimum in lung (54 days). Factors associated with prolonged ID (OR>92 days) were female sex, CRC or prostate location, localised stage, index primary care (AP) consultation and outpatient diagnostic pathway. Prolonged IT (OR>56 days) was related to CRC or prostate location and outpatient diagnostic route. ID components with the greatest influence on delay were: Primary Care Interval (IAP), Secondary Care Delay (DAS) and Secondary Care Adjunctive Test Delay (DPAS). The contribution of IAP was highest in patients with CRC, lung and bladder.

CONCLUSIONS

ID and IT were 92 and 56 days respectively. The ID components with the highest contribution to delay were IAP, DAS and DPAS. Increasing diagnostic capacity in PC and organising specific diagnostic and treatment pathways would shorten these intervals and allow earlier detection.

Analysis on the Effects of CT- and Ultrasound-Guided Percutaneous Transthoracic Needle Biopsy Combined with Serum CA125 and CEA on the Diagnosis of Lung Cancer

The number of patients with lung cancer is difficultly diagnosed in the early stage. The purpose of the study was to investigate the effects of CT- and ultrasound-guided percutaneous transthoracic needle biopsy combined with serum CA125 and CEA on the diagnosis of lung cancer. 120 patients with suspected lung cancer admitted to our hospital from January 2019 to January 2020 were selected and divided into an ultrasound group (n = 60) and CT group (n = 60), according to different percutaneous transthoracic needle biopsy modalities. All patients received serum tumor markers detection, so as to compare the CT- and ultrasound-guided percutaneous transthoracic needle biopsy results and pathology results, levels of serum tumor markers among all patients and the patients with different lung cancer types, and diagnostic efficacy of tumor markers, as well as complication rate (CR) in patients. The sensitivity and specificity of ultrasound-guided percutaneous transthoracic needle biopsy were 0.880 and 0.800, respectively, while those of CT-guided percutaneous transthoracic needle biopsy were 0.909 and 0.625, respectively; the CA125 and CEA levels in the lung cancer group were higher than those in the benign group (P < 0.001); the CA125 and CEA levels of the patients with adenocarcinoma were higher than those with squamous carcinoma, and the CEA levels of the patients with small-cell carcinoma were lower than those with adenocarcinoma (P < 0.05); the sensitivity, specificity, and Youden indexes of CA125 were 0.638, 0.833, and 0.471, respectively, while those of CEA were 0.766, 0.778, and 0.544, respectively; there were no significant differences in CR between the two groups (P > 0.05). CT- and ultrasound-guided percutaneous transthoracic needle biopsy is a safe and feasible diagnostic modality for lung cancer, and its combination with serum CA125 and CEA can significantly improve the accuracy of the detection results, which is worthy of promotion and application in clinical practice.

Using Electronic Medical Records to Identify Potentially Eligible Study Subjects for Lung Cancer Screening with Biomarkers

Lung cancer screening trials using low-dose computed tomography (LDCT) show reduced late-stage diagnosis and mortality rates. These trials have identified high-risk groups that would benefit from screening. However, these sub-populations can be difficult to access and retain in trials. Implementation of national screening programmes further suggests that there is poor uptake in eligible populations. A new approach to participant selection may be more effective. Electronic medical records (EMRs) are a viable alternative to population-based or health registries, as they contain detailed clinical and demographic information. Trials have identified that e-screening using EMRs has improved trial retention and eligible subject identification. As such, this paper argues for greater use of EMRs in trial recruitment and screening programmes. Moreover, this opinion paper explores the current issues in and approaches to lung cancer screening, whether records can be used to identify eligible subjects for screening and the challenges that researchers face when using EMR data.

Sensations, symptoms, and then what? Early bodily experiences prior to diagnosis of lung cancer

Lung cancer (LC) generally lacks unique core symptoms or signs. However, there are a multitude of bodily sensations that are often non-specific, not easily understood, and many times initially not recognized as indicative of LC by the affected person, which often leads to late diagnosis. In this international qualitative study, we inductively analyzed retrospective accounts of 61 people diagnosed with LC in Denmark, England and Sweden. Using the bodily sensations they most commonly spoke about (tiredness, breathlessness, pain, and cough), we constructed four sensation-based cases to understand the pre-diagnostic processes of reasoning and practice triggered by these key indicators of LC. We thereafter critically applied Hay's model of sensations to symptoms transformation, examining its central concepts of duration, disability and vulnerability, to support understanding of these processes. We found that while duration and disability are clearly relevant, vulnerability is more implicitly expressed in relation to perceived threat. Tiredness, even when of long duration and causing disability, was often related to normal aging, rather than a health threat. Regardless of duration, breathlessness was disturbing and threatening enough to lead to care-seeking. Pain varied by location, duration and degree of disability, and thus also varied in degree of threat perceived. Preconceived, but unmet expectations of what LC-related cough and pain would entail could cause delays by misleading participants; if cough lasted long enough, it could trigger health care contact. Duration, disability, and sense of threat, rather than vulnerability, were found to be relevant concepts for understanding the trajectory to diagnosis for LC among these participants. The process by which an individual, their family and health care providers legitimize sensations, allowing them to be seen as potential symptoms of disease, is also an essential, but varying part of the diagnostic processes described here.

A Narrative Review and Proposed Framework for Using Health System Data with Systematic Reviews to Support Decision-making

Systematic reviews are a necessary, but often insufficient, source of information to address the decision-making needs of health systems. In this paper, we address when and how the use of health system data might make systematic reviews more useful to decision-makers. We describe the different ways in which health system data can be used with systematic reviews, identify scenarios in which the addition of health system data may be most helpful (i.e., to improve the strength of evidence, to improve the applicability of evidence, and to inform the implementation of evidence), and discuss the importance of framing the limitations and considerations when using unpublished health system data in reviews. We developed a framework to guide the use of health system data alongside systematic reviews based on a narrative review of the literature and empirical experience. We also offer recommendations to improve the transparency of reporting when using health system data alongside systematic reviews including providing rationale for employing additional data, details on the data source, critical appraisal to understand study design biases as well as limitations in data and information quality, and how the unpublished data compares to the systematically reviewed data. Future methodological work on how best to handle internal and external validity concerns of health system data in the context of systematically reviewed data and work on developing infrastructure to do this type of work is needed.

Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model

The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered to patients referred for suspected LC. Respondents were included in the present analysis only if they later received a primary LC diagnosis or had no cancer; and inclusion of each descriptor required ≥4 observations. Fully-completed data from 506/670 individuals later diagnosed with primary LC (n = 311) or no cancer (n = 195) were modelled with orthogonal projections to latent structures (OPLS). After analysing 145/285 descriptors, meeting inclusion criteria, through randomised seven-fold cross-validation (six-fold training set: n = 433; test set: n = 73), 63 provided best LC prediction. The most-significant LC-positive descriptors included a cough that varied over the day, back pain/aches/discomfort, early satiety, appetite loss, and having less strength. Upon combining the descriptors with the background variables current smoking, a cold/flu or pneumonia within the past two years, female sex, older age, a history of COPD (positive LC-association); antibiotics within the past two years, and a history of pneumonia (negative LC-association); the resulting 70-variable model had accurate cross-validated test set performance: area under the ROC curve = 0.767 (descriptors only: 0.736/background predictors only: 0.652), sensitivity = 84.8% (73.9/76.1%, respectively), specificity = 55.6% (66.7/51.9%, respectively). In conclusion, accurate prediction of LC was found through 63 early symptoms/sensations and seven background factors. Further research and precision in this model may lead to a tool for referral and LC diagnostic decision-making.

Correction: Is symptom-based diagnosis of lung cancer possible? A systematic review and meta-analysis of symptomatic lung cancer prior to diagnosis for comparison with real-time data from routine general practice

[This corrects the article DOI: 10.1371/journal.pone.0207686.].