| 1. |
- Adnan, Ali, et al.
(author)
-
Health-related quality of life among tonsillar carcinoma patients in Sweden in relation to treatment and comparison with quality of life among the population
- 2020
-
In: Head and Neck-Journal for the Sciences and Specialties of the Head and Neck. - : Wiley. - 1043-3074 .- 1097-0347. ; 42:5, s. 860-872
-
Journal article (peer-reviewed)abstract
- Background The health-related quality of life (HRQOL) of tonsillar carcinoma survivors was explored to investigate any HRQOL differences associated with tumor stage and treatment. The survivors' HRQOL was also compared to reference scores from the population. Methods In this exploratory cross-sectional study patients were invited 15 months after their diagnosis and asked to answer two quality of life questionnaires (EORTC QLQ- C30, EORTC QLQ- HN35), 405 participated. Results HRQOL was associated with gender, with males scoring better than females on a few scales. Patients' HRQOL was more associated with treatment than tumor stage. Patients' HRQOL was worse than that in an age- and sex-matched reference group from the normal population, the largest differences were found for problems with dry mouth followed by problems with sticky saliva, senses, swallowing and appetite loss. Conclusions The tonsillar carcinoma patients had a worse HRQOL compared to the general population one year after treatment.
|
|
| 2. |
- Berg, Malin, 1976, et al.
(author)
-
A national study of health-related quality of life in patients with cancer of the base of the tongue compared to the general population and to patients with tonsillar carcinoma
- 2021
-
In: Head and Neck-Journal for the Sciences and Specialties of the Head and Neck. - : Wiley. - 1043-3074 .- 1097-0347. ; 43:12, s. 3843-3856
-
Journal article (peer-reviewed)abstract
- Background This exploratory, registry-based, cross-sectional study aimed to evaluate patients' health-related quality of life (HRQOL) in a subsite of oropharyngeal cancer: cancer of the base of the tongue (CBT). Methods CBT patients, treated with curative intent, completed the EORTC QLQ-C30 and QLQ-H&N35 questionnaires 15 months after diagnosis. The HRQOL of CBT patients was compared to reference scores from the general population and to that of tonsillar carcinoma patients. Results The 190 CBT patients scored significantly worse than members of the general population on most scales. CBT patients with human papilloma virus (HPV)-positive tumors had significantly better HRQOL on 8 of 28 scales than HPV-negative patients. Compared to 405 tonsillar carcinoma patients, CBT patients had significantly worse HRQOL on 8 of the 28 scales, the majority local head and neck related problems. Conclusion One year after treatment, CBT patients' HRQOL was significantly worse in many areas compared to that of the general population and slightly worse than that of tonsillar carcinoma patients.
|
|
| 3. |
- Boldrup, Linda, et al.
(author)
-
Levels of MUC1 in tumours and serum of patients with different sub-types of squamous cell carcinoma of the head and neck
- 2020
-
In: Oncology Letters. - : Spandidos Publications. - 1792-1074 .- 1792-1082. ; 20:2, s. 1709-1718
-
Journal article (peer-reviewed)abstract
- Mucin 1 (MUC1) is a membrane-bound and secreted glycoprotein that has a protective role in surface epithelia. We recently demonstrated that MUC1 mRNA expression was upregulated in tumour-free tongue tissues adjacent to squamous cell carcinoma of the oral tongue (SCCOT) compared with that in the tumour tissues. The present study investigated MUC1 protein in SCCOT tissue and serum from patients with squamous cell carcinoma of the head and neck (SCCHN) at different sub-sites. The results from immunohistochemistry demonstrated that all SCCOT tissues expressed MUC1; however, the protein levels were not correlated with MUC1 mRNA levels in the same tumours. Furthermore, serum MUC1 level was lower in patients with SCCOT, tonsil SCC and gingival SCC compared with that in healthy subjects; however, the difference was only significant for patients with SCCOT (P=0.0421). No correlation was seen between MUC1 level in tumour tissues and MUCI level in serum from the same patients. The absence of correlation between MUC1 protein and mRNA levels in SCCOT tissues emphasized the importance of validating genomic data in clinical samples. Although significant MUC1 downregulation was observed in the serum of patients with SCCOT, there was a large variation within the groups, suggesting that MUC1 may not be used as a biomarker for these types of tumors.
|
|
| 4. |
- Salehi, Amir M., 1971-
(author)
-
Clinical investigation and application of Artificial Intelligence in diagnosis and prognosis of squamous cell carcinoma of the head and neck
- 2023
-
Doctoral thesis (other academic/artistic)abstract
- Background: In Sweden around 1400 people are affected by head and neck cancer each year, and around 400 of these tumours are located in the mobile tongue (SCCOT). A major problem with these tumours is the high degree of relapse. In order to broaden our understanding of the group of squamous cell carcinoma of the head and neck (SCCHN) tumours we evaluated and compared the outcomes of panendoscopy with biopsy, ultrasonography with fine needle aspiration cytology (US-FNAC), and preoperative positron emission tomography/computed tomography (PET/CT) data from the same patients. As patients with SCCHN frequently have distant metastasis and locoregional recurrences, machine learning (ML) techniques were used to create classification models that accurately predict the likelihood of an early recurrence.Materials and methods: From patients suspected of having head and neck cancer between 2014–2016 results from PET/CT, panendoscopy with biopsy and US-FNAC were compared. Clinical, genomic, transcriptomic, and proteomic markers identifying recurrence risk were investigated. In blood samples taken from healthy individuals, data from proteins relevant to inflammation and/or tumor processes were evaluated. The SHapley Additive Explanations (SHAP) approach was used to determine the best ML algorithm for feature selection. AdaBoost, Artificial neural networks (ANNs), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) were used to create prediction models. Clinical data from patients were analyzed using statistical and ML techniques.Results: The concordance between results from PET/CT and panendoscopy with biopsy was 91.3%, and somewhat lower, 89.1%, for PET/CT and US-FNAC. The top contributors to classification with the ML approach were five mRNAs (PLAUR, DKK1, AXIN2, ANG, VEGFA), and 10 proteins (RAD50, 4E-BP1, MYH11, MAP2K1, BECN1, NF2, RAB25, ERRFI1, KDR, SERPINE1), using the extreme gradient boosting (XGBoost) method. The SHAP approach was used for feature selection. Using data from analysis of proteins in blood and interpretable ML showed that the Support Vector Machine (SVM) had the best performance with a balanced accuracy of 0.863, and a ROC-AUC of 0.924. The top three contributors to the SVM prediction model's performance were IL10, TNF Receptor Associated Factor 2 (TRAF2), and Kallikrein Related Peptidase 12 (KLK12). Recurrence was correlated with diabetes (p = 0.003), radiographic neck metastasis (p = 0.010), and T stage (p = 0.0012). A ML model got an accuracy rate of 71.2%. In the SCCOT group, diabetics predominated over non-diabetics, and also had lower recurrence rates and better survival (p = 0.012).Conclusion: Results show that the combination PET/CT is useful in diagnosis of SCCHN. It further emphasizes the use of ML to identify transcriptomic and proteomic factors that are significant in predicting risk of recurrence in patients with SCCHN. It provides a methodical strategy for early diagnosis of SCCOT before onset of clinical symptoms using multidimensional plasma protein profiling and interpretable ML. A model for predicting recurrence of SCCOT is provided by ML utilizing clinical data. As SCCOT patients with co-existing diabetes showed a better prognosis than non-diabetics, results suggest that individuals with SCCOT, regardless of diabetes status, may benefit from therapeutic management of glucose levels.
|
|
| 5. |
- Salehi, Amir M., et al.
(author)
-
Comparison of Preoperative Positron Emission Tomography/Computed Tomography with Panscopy and Ultrasound in Patients with Head and Neck Cancer
- 2020
-
In: Oncology. - : S. Karger. - 0030-2414 .- 1423-0232. ; 98:12, s. 889-892
-
Journal article (peer-reviewed)abstract
- Introduction: To compare data from preoperative positron emission tomography/computed tomography (PET/CT) with results of panscopy with biopsy and ultrasound with fine needle aspiration cytology (US-FNAC) on the same patients.Methods: In this retrospective (2014-2016) study, we compared PET/CT results with the results from panscopy with biopsy and US-FNAC in patients suspected of head and neck malignancy treated at the University Hospital in Umea, Sweden.Results: A 91.3% concordance was seen between results from PET/CT and panscopy with biopsy, whereas between PET/CT and US-FNAC the concordance was 89.1%.Conclusions: The present data show the usefulness of PET/CT in the diagnosis of head and neck malignancies.
|
|
| 6. |
- Salehi, Amir M., et al.
(author)
-
Comparison of Quality of Life among Patients with Oro-Hypopharyngeal Cancer after Tonsillectomy and Panscopy Using Transoral Robotic Surgery : A Pilot Study
- 2020
-
In: Case Reports in Oncology. - : S. Karger. - 1662-6575. ; 13:3, s. 1295-1303
-
Journal article (peer-reviewed)abstract
- Studies have shown lower treatment-related morbidity when using transoral robotic surgery (TORS) compared to conventional surgery. Patients investigated for oro- and hypopharyngeal cancer (T1, T2) were compared concerning quality of life (QoL) after tonsillectomy and TORS using validated QoL questionnaires: QLQ-C30 and QLQ-H&N35. The patients treated with TORS showed a higher pain score and thus also a higher need for painkillers, whereas they had lower values on self-assessment of anxiety/depression using the Hospital Anxiety and Depression Scale score. The pre- and postoperative information given did not meet the expectations of the patients treated with conventional surgery. The present data show advantages of the TORS technique from the patients' perspective. Even if patients treated with TORS are in need of more painkilling treatment, they cope better with the long-term effects of treatment, as judged by self-assessment of anxiety and depression.
|
|
| 7. |
- Salehi, Amir M., et al.
(author)
-
Patients with oral tongue squamous cell carcinoma and co‑existing diabetes exhibit lower recurrence rates and improved survival : implications for treatment
- 2024
-
In: Oncology Letters. - : Spandidos Publications. - 1792-1074 .- 1792-1082. ; 27:4
-
Journal article (peer-reviewed)abstract
- Locoregional recurrences and distant metastases are major problems for patients with squamous cell carcinoma of the head and neck (SCCHN). Because SCCHN is a heterogeneous group of tumours with varying characteristics, the present study concentrated on the subgroup of squamous cell carcinoma of the oral tongue (SCCOT) to investigate the use of machine learning approaches to predict the risk of recurrence from routine clinical data available at diagnosis. The approach also identified the most important parameters that identify and classify recurrence risk. A total of 66 patients with SCCOT were included. Clinical data available at diagnosis were analysed using statistical analysis and machine learning approaches. Tumour recurrence was associated with T stage (P=0.001), radiological neck metastasis (P=0.010) and diabetes (P=0.003). A machine learning model based on the random forest algorithm and with attendant explainability was used. Whilst patients with diabetes were overrepresented in the SCCOT cohort, diabetics had lower recur‑ rence rates (P=0.015 after adjusting for age and other clinical features) and an improved 2‑year survival (P=0.025) compared with non‑diabetics. Clinical, radiological and histological data available at diagnosis were used to establish a prognostic model for patients with SCCOT. Using machine learning to predict recurrence produced a classification model with 71.2% accuracy. Notably, one of the findings of the feature importance rankings of the model was that diabetics exhibited less recur‑ rence and improved survival compared with non‑diabetics, even after accounting for the independent prognostic variables of tumour size and patient age at diagnosis. These data imply that the therapeutic manipulation of glucose levels used to treatdiabetes may be useful for patients with SCCOT regardless of their diabetic status. Further studies are warranted to investigatethe impact of diabetes in other SCCHN subtypes.
|
|
| 8. |
- Salehi, Amir M., et al.
(author)
-
Reiterative modeling of combined transcriptomic and proteomic features refines and improves the prediction of early recurrence in squamous cell carcinoma of head and neck
- 2022
-
In: Computers in Biology and Medicine. - : Elsevier. - 0010-4825 .- 1879-0534. ; 149
-
Journal article (peer-reviewed)abstract
- Background: Patients with squamous cell carcinoma of the head and neck (SCCHN) have a high-risk of recurrence. We aimed to develop machine learning methods to identify transcriptomic and proteomic features that provide accurate classification models for predicting risk of early recurrence in SCCHN patients.Methods: Clinical, genomic, transcriptomic and proteomic features distinguishing recurrence risk were examined in SCCHN patients from The Cancer Genome Atlas (TCGA). Recurrence within one year after treatment was classified as high-risk and no recurrence as low-risk.Results: No significant differences in individual clinicopathological characteristics, mutation profiles or mRNA expression patterns were seen between the groups using conventional statistical analysis. Using the machine learning algorithm, extreme gradient boosting (XGBoost), ten proteins (RAD50, 4E-BP1, MYH11, MAP2K1, BECN1, NF2, RAB25, ERRFI1, KDR, SERPINE1) and five mRNAs (PLAUR, DKK1, AXIN2, ANG and VEGFA) made the greatest contribution to classification. These features were used to build improved models in XGBoost, achieving the best discrimination performance when combining transcriptomic and proteomic data, providing an accuracy of 0.939 and an Area Under the ROC Curve (AUC) of 0.951.Conclusions: This study highlights machine learning to identify transcriptomic and proteomic factors that play important roles in predicting risk of recurrence in patients with SCCHN and to develop such models by iterative cycles to enhance their accuracy, thereby aiding the introduction of personalized treatment regimens.
|
|
| 9. |
- Wilms, Torben, et al.
(author)
-
PD-L1 in squamous cell carcinoma of the oral tongue shows gender-specific association with prognosis
- 2020
-
In: Oral Diseases. - : John Wiley & Sons. - 1354-523X .- 1601-0825. ; 26:7, s. 1414-1423
-
Journal article (peer-reviewed)abstract
- Objective: To use alternative quantitation approaches to clarify the clinical implication of programmed cell death ligand 1 (PD‐L1) in squamous cell carcinoma of the oral tongue (SCCOT).Materials and Methods: Ventana SP263 immunohistochemistry assay and a multiplicative QuickScore method were applied to quantify PD‐L1 in tumor and surrounding immune cells from 101 patients with SCCOT. Tumor‐infiltrating immune cells were estimated from bulk tissue transcriptional profiles of 25 patients. Circulating PD‐L1 levels were measured in serum from 30 patients using an electrochemiluminescence assay platform.Results: We found higher tumor cell PD‐L1 levels in females than males (p = .019). For patients with low PD‐L1 in tumor cells, better survival was seen in males than females (overall survival p = .021, disease‐free survival p = .020). Tumor‐infiltrating natural killer T cells, immature dendritic cells, and M1 macrophages were positively associated with tumor cell PD‐L1 (p < .05).Conclusions: Our data confirmed the significance of gender on tumor cell PD‐L1 expression and demonstrated combined effects of gender and PD‐L1 levels on clinical outcome in patients with SCCOT. The data also indicated the involvement of specific immune cell types in PD‐L1‐regulated immune evasion.
|
|
