Consistency of recording of chemotherapy cycles in the National Cancer Registration and Analysis Service Systemic Anti-Cancer Therapy database and the Hospital Episode Statistics Admitted Patient Care database

2020 ◽  
Vol 16 (3) ◽  
pp. 4455-4460
Author(s):  
Laura McDonald ◽  
Cormac Sammon ◽  
Robert Carroll ◽  
Akash Harish ◽  
Abhishek Shankar C ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Therapy ◽  
Patient Care ◽  
Cancer Patients ◽  
Hospital Episode Statistics ◽  
Cancer Registration ◽  
Hospital Episode ◽  
Lung Cancer Patients ◽  
Anti Cancer ◽  
Care Database

Aim: We assessed the extent to which chemotherapy cycles recorded in Hospital Episode Statistics (HES) Admitted Patient Care (APC) were captured in National Cancer Registration & Analysis Service Systemic Anti-Cancer Therapy (SACT) for a cohort of lung cancer patients. Methods: All chemotherapy cycles recorded for linkage eligible lung cancer patients with a National Cancer Registration & Analysis Service diagnosis between 2012 and 2015 were identified in HES APC and SACT. Results: Among a population of 4070 lung cancer patients, 6076 chemotherapy cycles were observed in HES APC data. A total of 61% of cycles were recorded in SACT on the same day, 8% on a different day and 31% were not recorded in SACT. Conclusion: Our results suggest that SACT may not capture all chemotherapy cycles administered to a patient between 2012 and 2016; however, administrative changes mean data after this period may be more complete.

scholarly journals Linking the Diagnostic Imaging Dataset (DID) to Hospital Episode Statistics (HES) – improving and understanding the diagnosis of lung cancer

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
David Kennedy ◽  
Abigail Bentley ◽  
Erika Denton ◽  
Ella Ohuma ◽  
Nick Ormison-Smith ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Diagnostic Imaging ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Emergency Admission ◽  
Hospital Episode Statistics ◽  
X Rays ◽  
Hospital Episode ◽  
Lung Cancer Patients ◽  
Lung Cancer Diagnosis

ABSTRACT ObjectivesTo link the Diagnostic Imaging Dataset (DID) to Hospital Episode Statistics (HES) to explore the association between patient imaging and hospital based care and outcomes for cancer patients in English NHS hospitals. This is the first time this linkage has taken place. The analysis also aims to look at how each patient first presented in HES (A&E, emergency admission, elective care, regular attendance), when and by what route relevant tests were requested and geographic variation in access to imaging ApproachPatient imaging records from the DID were linked to HES databases containing details of all inpatient, outpatient and A&E admissions at NHS hospitals in England in 2012/13 and 2013/14. Match rank criteria were developed to ensure that patients in HES were accurately linked to patients in DID by NHS number, date of birth and other unique identifiers. We used HES to identify patients with a lung cancer diagnosis and investigate their use of imaging and the temporal nature of tests to evaluate whether patients were following recommended pathways (e.g. having chest x-rays followed by CT scans before their lung cancer diagnosis) and the time between these events. Lung cancer patients were identified by developing an algorithm to search through diagnostic fields for clinical codes within HES databases. Where there was a lung cancer code the record was flagged and subsequently extracted. ResultsThe combined HES and DID datasets consisted of more than 340 million records. Within this large dataset we identified 49,888 patients with a lung cancer code in one of their HES diagnosis fields to a DID diagnostic image record for inpatient records alone. A high proportion (97%) of records were matched in one of the top 3 rank levels, suggesting the linkage was successful. The results illustrate the relationship between the imaging referral pathway and hospital episodes (e.g. surgical resection, emergency presentation). ConclusionInvestigating how people engage with imaging services and hospital care will increase our understanding of the pathways associated with lung cancer diagnosis. The results from this analysis will contribute new knowledge about how lung cancer patients interact with hospitals and imaging services.

110: Drug interactions with systemic anti-cancer therapy in lung cancer patients

Lung Cancer ◽  
2017 ◽  
Vol 103 ◽  
pp. S49-S50
Author(s):  
R. Panchal ◽  
E. Ward ◽  
V. Marvin ◽  
T. Newsom-Davis ◽  
M. Bower ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Therapy ◽  
Drug Interactions ◽  
Cancer Patients ◽  
Lung Cancer Patients ◽  
Anti Cancer

scholarly journals Developing an intervention to support lung cancer patients and their clinicians when considering systemic anti-cancer therapy: pact study

Trials ◽  
2013 ◽  
Vol 14 (S1) ◽  
Author(s):  
Annmarie Nelson ◽  
Stephanie Sivell ◽  
Simon Noble ◽  
Anthony Byrne ◽  
Jason Lester
Keyword(s):  
Lung Cancer ◽  
Cancer Therapy ◽  
Cancer Patients ◽  
Lung Cancer Patients ◽  
Anti Cancer

scholarly journals The M1/M2 spectrum and plasticity of malignant pleural effusion-macrophage in advanced lung cancer

2020 ◽  
Author(s):  
Ming-Fang Wu ◽  
Chih-An Lin ◽  
Tzu-Hang Yuan ◽  
Hsiang-Yuan Yeh ◽  
Sheng-Fang Su ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pleural Effusion ◽  
Lung Adenocarcinoma ◽  
Cancer Patients ◽  
Patient Outcomes ◽  
Malignant Pleural Effusion ◽  
Advanced Lung Cancer ◽  
Lung Cancer Patients ◽  
Anti Cancer ◽  
Cancer Activity

Abstract Background Malignant pleural effusion (MPE)-macrophage (Mφ) of lung cancer patients within unique M1/M2 spectrum showed plasticity in M1–M2 transition. The M1/M2 features of MPE-Mφ and their significance to patient outcomes need to be clarified; furthermore, whether M1-repolarization could benefit treatment remains unclear. Methods Total 147 stage-IV lung adenocarcinoma patients undergoing MPE drainage were enrolled for profiling and validation of their M1/M2 spectrum. In addition, the MPE-Mφ signature on overall patient survival was analyzed. The impact of the M1-polarization strategy of patient-derived MPE-Mφ on anti-cancer activity was examined. Results We found that MPE-Mφ expressed both traditional M1 (HLA-DRA) and M2 (CD163) markers and showed a wide range of M1/M2 spectrum. Most of the MPE-Mφ displayed diverse PD-L1 expression patterns, while the low PD-L1 expression group was correlated with higher levels of IL-10. Among these markers, we identified a novel two-gene MPE-Mφ signature, IL-1β and TGF-β1, representing the M1/M2 tendency, which showed a strong predictive power in patient outcomes in our MPE-Mφ patient cohort (N = 60, p = 0.013) and The Cancer Genome Atlas Lung Adenocarcinoma dataset (N = 478, p < 0.0001). Significantly, β-glucan worked synergistically with IFN-γ to reverse the risk signature by repolarizing the MPE-Mφ toward the M1 pattern, enhancing anti-cancer activity. Conclusions We identified MPE-Mφ on the M1/M2 spectrum and plasticity and described a two-gene M1/M2 signature that could predict the outcome of late-stage lung cancer patients. In addition, we found that “re-education” of these MPE-Mφ toward anti-cancer M1 macrophages using clinically applicable strategies may overcome tumor immune escape and benefit anti-cancer therapies.

scholarly journals Advancing Personalized Cancer Medicine in Lung Cancer

2012 ◽  
Vol 136 (10) ◽  
pp. 1210-1216 ◽  
Author(s):  
Laura E. MacConaill
Keyword(s):  
Lung Cancer ◽  
Cancer Therapy ◽  
Cancer Patients ◽  
Lung Cancer Patients ◽  
The Past ◽  
Genomic Technologies ◽  
Personalized Cancer Medicine ◽  
Cancer Medicine ◽  
Personalized Cancer Therapy ◽  
Personalized Cancer

Although improvements in genomic technologies during the past decade have greatly advanced our understanding of the genomic alterations that contribute to lung cancer, and the disease has (to a degree) become a paradigm for individualized cancer treatment in solid tumors, additional challenges must be addressed before the goal of personalized cancer therapy can become a reality for lung cancer patients.

scholarly journals The effect of anti-cancer and anti-tuberculosis treatments in lung cancer patients with active tuberculosis: a retrospective analysis

2020 ◽  
Author(s):  
MEI CHAI ◽  
Qingming Shi
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Side Effect ◽  
Treatment Completion ◽  
Completion Rate ◽  
Karnofsky Performance Score ◽  
Lung Cancer Patients ◽  
Control Subjects ◽  
Tb Treatment ◽  
Anti Cancer

Abstract Background Lung tuberculosis (TB) and lung cancer have a complex relationship. Data concerning TB treatment in lung cancer patients are still incomplete. The aim of this study was to investigate the effects of anti-cancer and anti-tuberculosis treatments in lung cancer patients with active lung TB. Methods In a retrospective cohort study, lung cancer patients with active lung TB were identified between January 2013 and December 2016. Age- and sex-matched lung cancer patients without tuberculosis were selected as control subjects. Anti-cancer and anti-tuberculosis treatments were administered according to the national guidelines. The clinical courses and responses of lung cancer patients with and without active lung TB were examined and compared.Results A total of 31 consecutive lung cancer patients were diagnosed with active lung TB. Fifty-one lung cancer patients without TB were enrolled as control subjects. Most patients in the two groups were elderly, had advanced non-small cell lung cancer and had tumor burdens. The anti-cancer treatment completion rate and response rate were not different between two group (87.1% in TB treatment patients vs. 92.2% in lung cancer patients; 77.4% in TB treatment patients vs. 88.2% in lung cancer patients, respectively). The anti-tuberculosis treatment completion rate and success rate was 87.1% and 80.7%. The median survival times were not different between two groups (52 weeks in TB treatment patients vs. 57 weeks in lung cancer patients). The change in Karnofsky performance score was also not different between two groups. The most common side effect in TB treatment patients was liver injury (61.3%). The most serious side effect in TB treatment patients was leukocyte deficiency (9.7% in Grade 3). Both of side effects mentioned above were not different between two groups. Conclusion Both anti-cancer and anti-tuberculosis treatments can be safely and effectively administered in lung cancer patients with active lung TB. Attention should be paid to the risk of tuberculosis in lung cancer patients in TB high-burden countries.

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