Lung Cancer: New Directions in Senior Patients Assessment
Abstract
:1. Introduction
Literature Search and Selection Methodology
2. Biomarkers and Biological Reactivity in Lung Cancer Senior Patients
2.1. Biomarkers Used in the Diagnosis, Prognosis, and Treatment of Lung Cancer
2.2. Biomarkers in Lung Cancer Specific to Geriatric Patients
2.2.1. MicroRNA
2.2.2. Circulating Tumor DNA
2.2.3. DNA Methylation Age of Blood
3. Performance Status, Nutritional Status, Albumin Levels, and Individualization of Therapeutic Approach
4. Geriatric Lung Cancer Screening Tools
4.1. Clinical Toolkits and Assessment Tools—Geriatric 8, Identification of Seniors at Risk—Hospitalized Patients (ISAR-HPs), and Comprehensive Geriatric Assessment (CGA)
4.2. The Role of Geriatric Screening Instruments in Lung Cancer Assessment
4.3. Other Screening Tools and Assessments
5. Discussion
5.1. The Implications of Biomarkers in Lung Cancer Management
5.1.1. Biomarkers Used in the Diagnosis, Prognosis, and Treatment of Lung Cancer
5.1.2. Biomarkers in Lung Cancer Specific to Geriatric Patients
- MicroRNA
- Circulating Tumor DNA
- DNA Methylation Age of Blood
5.2. Performance Status, Nutritional Status, Albumin Levels, and Individualization of Therapeutic Approach
5.3. The Value of Clinical Toolkits and Assessment Tools in Managing Senior Patients
5.3.1. The Role of Geriatric Screening Instruments in Lung Cancer Assessment
5.3.2. Other Screening Tools and Assessments
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Acronym | Biomarker | Description |
---|---|---|
EGFR | Epidermal Growth Factor Receptor | Mutations in the EGFR gene are common in non-small-cell lung cancer (NSCLC) and are important for selecting patients for EGFR tyrosine kinase inhibitor therapy. |
ALK | Anaplastic Lymphoma Kinase | Rearrangements in the ALK gene are found in a subset of NSCLC patients, and these patients may benefit from ALK inhibitors. |
KRAS | Kirsten Rat Sarcoma Viral Oncogene | KRAS mutations are common in lung cancer and have been associated with resistance to certain therapies, although new treatments targeting specific KRAS mutations are emerging. |
ROS1 | C-ros Oncogene 1 | Like ALK, ROS1 rearrangements can predict responsiveness to specific targeted therapies in NSCLC. |
BRAF | Proto-Oncogene B-Raf | Mutations in the BRAF gene, particularly V600E, can be targeted with specific inhibitors in NSCLC. |
PD-L1 | Programmed Death-Ligand 1 | The expression level of PD-L1 can predict the response to PD-1/PD-L1 checkpoint inhibitors in lung cancer. |
HER2 | Human Epidermal Growth Factor Receptor 2 | While less common, HER2 mutations can be targeted with specific therapies in NSCLC. |
MET | Mesenchymal–Epithelial Transition | MET exon 14 skipping mutations and MET amplification can influence treatment options in NSCLC. |
RET | Rearranged during transfection | Rearrangements in the RET gene can be targeted with RET inhibitors in NSCLC. |
P53 | Tumor Suppression Gene P 53 | Mutations in P53 are common in lung cancer and can have prognostic significance. |
TMB | Tumor Mutational Burden | High TMB can predict responsiveness to immunotherapy in some lung cancer settings. |
MSI | Microsatellite Instability | Although rarer in lung cancer, these biomarkers can predict response to immunotherapy [11]. |
dMMR | Mismatch Repair Deficiency | Although rarer in lung cancer, these biomarkers can predict response to immunotherapy [11]. |
Items | Possible Responses (Score) |
---|---|
| 0 = severe decrease in food intake |
1 = moderate decrease in food intake | |
2 = no decrease in food intake | |
| 0 = weight loss > 3 kg |
1 = does not know | |
2 = weight loss between 1 and 3 kg | |
3 = no weight loss | |
| 3 = no weight loss |
0 = bed or chair bound | |
1 = able to get out of bed/chair but does not go out | |
2 = goes out | |
| 0 = severe dementia or depression |
1 = mild dementia | |
2 = no psychological problems | |
| 0 = BMI < 19 |
1 = BMI 19 to <21 | |
2 = BMI 21 to <23 | |
3 = BMI ≥ 23 | |
| 0 = yes |
1 = no | |
| 0.0 = not as good |
0.5 = does not know | |
1.0 = as good | |
2.0 = better | |
Age | 0: >85 |
1: 80–95 | |
2: <80 | |
Total score | 0–17 |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Pîslaru, A.I.; Albișteanu, S.-M.; Ilie, A.C.; Ștefaniu, R.; Mârza, A.; Moscaliuc, Ș.; Nicoară, M.; Turcu, A.-M.; Grigoraș, G.; Alexa, I.D. Lung Cancer: New Directions in Senior Patients Assessment. Geriatrics 2024, 9, 101. https://doi.org/10.3390/geriatrics9040101
Pîslaru AI, Albișteanu S-M, Ilie AC, Ștefaniu R, Mârza A, Moscaliuc Ș, Nicoară M, Turcu A-M, Grigoraș G, Alexa ID. Lung Cancer: New Directions in Senior Patients Assessment. Geriatrics. 2024; 9(4):101. https://doi.org/10.3390/geriatrics9040101
Chicago/Turabian StylePîslaru, Anca Iuliana, Sabinne-Marie Albișteanu, Adina Carmen Ilie, Ramona Ștefaniu, Aurelia Mârza, Ștefan Moscaliuc, Mălina Nicoară, Ana-Maria Turcu, Gabriela Grigoraș, and Ioana Dana Alexa. 2024. "Lung Cancer: New Directions in Senior Patients Assessment" Geriatrics 9, no. 4: 101. https://doi.org/10.3390/geriatrics9040101