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Lazzaro C, Fattore G, Barberis M, Buttitta F, Cassoni P, Graziano P, Marchetti A, Crema S, Dal Pero F, Papotti MG. Full cost of diagnostic pathology for lung carcinoma in Italy: results from four Pathology Units. Pathologica 2023; 115:83-89. [PMID: 36790110 PMCID: PMC10463002 DOI: 10.32074/1591-951x-837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 12/07/2022] [Indexed: 02/16/2023] Open
Abstract
Objective To calculate the full cost of diagnostic pathology tests for Non-Small Cell Lung Cancer (NSCLC) across four Italian Pathology Units. Methods Pathology Units were located in private (2) and public (2) hospitals distributed across the Italian territory (North: 2; Centre: 1; South: 1). Pathologists provided via questionnaire data on tests on NSCLC samples along with the identification and quantification of the necessary healthcare resources (diagnostic technologies, laboratory instruments and personnel). Resources were valued according to hospital-specific unit, yearly and hourly costs (disposables; technologies; professional clusters). Results The full cost per NSCLC tissue sample included histopathological immunophenotypic and required molecular analysis. Overall, it reached € 659.77 and it was mainly composed of direct costs (77.69%). The processing of a NSCLC tissue sample was labour intensive, as a relevant share of the full cost (44.98%) was actually due to personnel costs, with laboratory technicians, biologists and pathologist driving this finding (17.09%,12.43% and 10.81%, respectively). Conclusions The results of this research can facilitate the negotiation of new dedicated tariffs for NSCLC sample processing with the national or local third party-payers.
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Affiliation(s)
- Carlo Lazzaro
- Studio di Economia Sanitaria, Milan, Italy
- School of Pharmacology, Biology and Biotechnologies Department “Lazzaro Spallanzani”, University of Pavia, Pavia, Italy
| | - Giovanni Fattore
- Department of Social and Political Sciences, Università “Luigi Bocconi”, Milan, Italy
- CeRGAS, Centre for Research on Health and Social Care Management-SDA, Università “Luigi Bocconi”, Milan, Italy
| | - Massimo Barberis
- Division of Pathology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Fiamma Buttitta
- Laboratory of Molecular Diagnostics, Center for Advanced Studies and Technology (CAST), University of Chieti-Pescara, Italy
| | - Paola Cassoni
- Division of Pathology, University of Turin, Turin, Italy
| | - Paolo Graziano
- Pathology Unit, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy
| | - Antonio Marchetti
- Laboratory of Molecular Diagnostics, Center for Advanced Studies and Technology (CAST), University of Chieti-Pescara, Italy
| | - Stefania Crema
- Digital Customer Success Manager, Roche Diagnostics S.p.A., Monza, Italy
| | - Francesca Dal Pero
- National Sales RTD Seq & Lab Consulting, Roche Diagnostics S.p.A., Monza, Italy
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Nadal E, Bautista D, Cabezón-Gutiérrez L, Ortega AL, Torres H, Carcedo D, Ruiz de Alda L, Garcia JF, Vieitez P, Rojo F. Clinical and economic impact of current ALK rearrangement testing in Spain compared with a hypothetical no-testing scenario. BMC Cancer 2021; 21:689. [PMID: 34112097 PMCID: PMC8194132 DOI: 10.1186/s12885-021-08407-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/25/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Currently biomarkers play an essential role in diagnosis, treatment, and management of cancer. In non-small cell lung cancer (NSCLC) determination of biomarkers such as ALK, EGFR, ROS1 or PD-L1 is mandatory for an adequate treatment decision. The aim of this study is to determine the clinical and economic impact of current anaplastic lymphoma kinase testing scenario in Spain. METHODS A joint model, composed by decision-tree and Markov models, was developed to estimate the long-term health outcomes and costs of NSCLC patients, by comparing the current testing scenario for ALK in Spain vs a hypothetical no-testing. The current distribution of testing strategies for ALK determination and their sensitivity and specificity data were obtained from the literature. Treatment allocation based on the molecular testing result were defined by a panel of Spanish experts. To assess long-term effects of each treatment, 3-states Markov models were developed, where progression-free survival and overall survival curves were extrapolated using exponential models. Medical direct costs (expressed in €, 2019) were included. A lifetime horizon was used and a discount rate of 3% was applied for both costs and health effects. Several sensitivity analyses, both deterministic and probabilistic, were performed in order test the robustness of the analysis. RESULTS We estimated a target population of 7628 NSCLC patients, including those with non-squamous histology and those with squamous carcinomas who were never smokers. Over the lifetime horizon, the current ALK testing scenario produced additional 5060 and 3906 life-years and quality-adjusted life-years (QALY), respectively, compared with the no-testing scenario. Total direct costs were increased up to € 51,319,053 for testing scenario. The incremental cost-effectiveness ratio was 10,142 €/QALY. The sensitivity analyses carried out confirmed the robustness of the base-case results, being the treatment allocation and the test accuracy (sensitivity and specificity data) the key drivers of the model. CONCLUSIONS ALK testing in advanced NSCLC patients, non-squamous and never-smoker squamous, provides more than 3000 QALYs in Spain over a lifetime horizon. Comparing this gain in health outcomes with the incremental costs, the resulting incremental cost-effectiveness ratio reinforces that testing non-squamous and never-smoker squamous NSCLC is a cost-effective strategy in Spain.
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Affiliation(s)
- Ernest Nadal
- Catalan Institute of Oncology, Hospital Duran i Reynals, IDIBELL, L'Hospitalet de Llobregat, Spain
| | | | | | | | - Héctor Torres
- Hospital Universitario Central de Asturias, Oviedo, Spain
| | | | | | | | | | - Federico Rojo
- Hospital Universitario Fundacion Jimenez Diaz - CIBERONC, Madrid, Spain
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Song L, Zhu Z, Wu H, Han W, Cheng X, Li J, Du H, Lei J, Sui X, Song W, Jin ZY. Individualized nomogram for predicting ALK rearrangement status in lung adenocarcinoma patients. Eur Radiol 2020; 31:2034-2047. [PMID: 33146791 DOI: 10.1007/s00330-020-07331-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/02/2020] [Accepted: 09/21/2020] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To develop a nomogram to identify anaplastic lymphoma kinase (ALK) mutations in lung adenocarcinoma patients using clinical, CT, PET/CT, and histopathological features. METHODS This retrospective study included 399 lung adenocarcinoma patients (129 ALK-rearranged patients and 270 ALK-negative patients) that were randomly divided into a training cohort and an internal validation cohort (4:1 ratio). Clinical factors, radiologist-defined CT features, maximum standard uptake values (SUVmax), and histopathological features were used to construct predictive models with stepwise backward-selection multivariate logistic regression (MLR). The models were then evaluated using the AUC. The integrated model was compared to the clinico-radiological model using the DeLong test to evaluate the role of histopathological features. An associated individualized nomogram was established. RESULTS The integrated model reached an AUC of 0.918 (95% CI, 0.886-0.950), sensitivity of 0.774, and specificity of 0.934 in the training cohort and an AUC of 0.857 (95% CI, 0.777-0.937), sensitivity of 0.739, and specificity of 0.810 in the validation cohort. The MLR analysis showed that younger age, never smoker, lymph node enlargement, the presence of cavity, high SUVmax, solid or micropapillary predominant histology subtype, and local invasiveness were strong and independent predictors of ALK rearrangements. The nomogram calculated the risk of harboring ALK mutation for lung adenocarcinoma patients and exhibited a good generalization ability. CONCLUSION Our study demonstrates that histopathological features added value to the imaging characteristics-based model. The nomogram with clinical, imaging, and histopathological features can serve as a supplementary non-invasive tool to evaluate the probability of ALK rearrangement in lung adenocarcinoma. KEY POINTS • The developed nomogram can accurately predict the probability of lung adenocarcinoma harboring ALK-fused gene. • Pathological analysis is important to predict ALK rearrangement in lung adenocarcinoma. • Lung adenocarcinoma with lepidic predominant growth pattern and TTF-1 negativity is unlikely to have ALK rearrangement.
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Affiliation(s)
- Lan Song
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China
| | - Zhenchen Zhu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.,4+4 MD Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Huanwen Wu
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Wei Han
- Department of Epidemiology and Biostatistics, Institute of Basic Medicine Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China
| | - Xin Cheng
- Department of Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Ji Li
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Huayang Du
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China
| | - Jing Lei
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China
| | - Xin Sui
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China
| | - Wei Song
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
| | - Zheng-Yu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
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