Dataset Information

Prognostic Factors Predict Oncological Outcome in Older Patients With Head and Neck Cancer Undergoing Chemoradiation Treatment.

ABSTRACT:

Purpose

Older patients with head and neck cancer (HNC) represent a challenging group, as frailty and comorbidities need to be considered. This study aimed to evaluate the efficacy and side effects of curative and palliative (chemo) radiation ([C]RT) with regard to basic geriatric screening in older patients.

Methods

This study included HNC patients aged ?70 years who were treated with curative or palliative (C)RT. Clinicopathological data including Charlson Comorbidity Index (CCI), Karnofsky performance status (KPS), and treatment data were analyzed as predictors of overall survival (OS).

Results

A total of 271 patients (median age, 74 years) were enrolled. The majority had UICC stage III/IV (90%) and underwent curative treatment (85.2%). A total of 144 (53.1%) patients received definitive and 87 (32.1%) had adjuvant (C)RT. Overall, 40 patients (14.8%) received palliative (C)RT. Median follow-up duration (curative setting) was 87 months, and the 2- and 5-year OS rates were 57.8 and 35.9%, respectively. Median OS was significantly different for age ?75 vs. >75 years, CCI <6 vs. ?6, KPS ?70 vs. <70%, Tx/T1/T2 vs. T3/T4, and adjuvant vs. definitive (C)RT, respectively. Age 70-75 years (p = 0.004), fewer comorbidities when CCI < 6 (p = 0.014), good KPS ? 70% (p = 0.001), and adjuvant (C)RT (p = 0.008) independently predicted longer survival. Palliative RT resulted in a median OS of 4 months.

Conclusion

Older age, lower KPS, higher CCI, and definitive (C)RT are indicators of worse survival in older patients with HNC treated curatively. Without a comprehensive geriatric assessment in patients aged >75 years, the KPS and CCI can be useful tools to account for "fitness, vulnerability or frailty" to help in treatment decision-making.

SUBMITTER: Stromberger C

PROVIDER: S-EPMC7942196 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prognostic Factors Predict Oncological Outcome in Older Patients With Head and Neck Cancer Undergoing Chemoradiation Treatment.

Stromberger Carmen C Yedikat Berna B Coordes Annekatrin A Tinhofer Ingeborg I Kalinauskaite Goda G Budach Volker V Zschaeck Sebastian S Raguse Jan-Dirk JD Kofla Grzegorz G Heiland Max M Stsefanenka Aksana A Beck-Broichsitter Benedicta B Dommerich Steffen S Senger Carolin C Beck Marcus M

Frontiers in oncology 20210223

<h4>Purpose</h4>Older patients with head and neck cancer (HNC) represent a challenging group, as frailty and comorbidities need to be considered. This study aimed to evaluate the efficacy and side effects of curative and palliative (chemo) radiation ([C]RT) with regard to basic geriatric screening in older patients.<h4>Methods</h4>This study included HNC patients aged ≥70 years who were treated with curative or palliative (C)RT. Clinicopathological data including Charlson Comorbidity Index (CCI) ...[more]

PMID: 33708616

Similar Datasets

Project description:Importance:Clinicians should understand the prevalence of depression and decision regret in patients with head and neck cancer and whether these factors differ with age or frailty. Objectives:To assess whether age and frailty are associated with preoperative and/or worsening postoperative depression and postoperative decision regret in patients undergoing major head and neck surgery and to identify additional factors associated with depression and decision regret. Design, Setting, and Participants:This prospective cohort study was conducted at a single institution, with patients aged 50 years or older undergoing major head and neck surgery recruited from December 1, 2011, to April 30, 2014. Statistical analysis was performed from July 1, 2018, to June 30, 2019. Main Outcomes and Measures:Frailty, functional, and geriatric depression assessments were completed before surgery and 3, 6, and 12 months after surgery. Decision regret assessment was completed 6 months after surgery. The prevalence of depression and decision regret was determined by age group. Change in depression over time was compared between age groups using a linear-effects model. Variables potentially associated with moderate to severe depression and decision regret were analyzed using a logistic regression model. Results:The study included 274 patients (68 women and 206 men; mean [SD] age, 67.8 [9.5] years). Of these, 105 (38.3%) were 50 to 64 years of age and 169 (61.7%) were 65 years or older. The rate of preoperative moderate to severe depression was 9.6% (21 of 219), with no difference between younger and older adult cohorts. For both age groups, depression scores increased in the postoperative period from baseline to 6 months. At 12 months, there was a difference in depression scores between the younger and older adult cohort (4.8 [4.6] vs 3.1 [3.6]). A higher preoperative Fried Frailty Index score (odds ratio, 2.58 [95% CI, 1.63-4.06]) was associated with preoperative moderate to severe depression. For all patients, the mean Decision Regret Scale score was 18.2 (range, 0-95), and 26.7% of patients (48 of 180) had moderate to severe regret. There was no difference in Decision Regret Scale scores between younger and older patients. Preoperative depression but not frailty is associated with postoperative moderate to severe decision regret (odds ratio, 1.17 [95% CI, 1.06-1.28]). Conclusions and Relevance:In this cohort study, there was no difference based on age in the prevalence of moderate to severe depression or decision regret. A higher preoperative frailty score was associated with depression but not decision regret. Preoperative depression was the only factor associated with moderate to severe decision regret on multivariate analysis. Understanding the prevalence of and factors associated with moderate to severe depression and decision regret may aid in identifying patients who would benefit from more extensive preoperative counseling and preoperative and postoperative multispecialty assessment and treatment.

Project description:BackgroundTranscriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.Materials and methodsGene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.ResultsWe identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.ConclusionThe six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.

Project description:Tumor-associated hypoxia influences the radiation response of head-and-neck cancer (HNSCC) patients, and a lack of early hypoxia resolution during treatment considerably deteriorates outcomes. As the detrimental effects of hypoxia are partly related to the induction of an immunosuppressive microenvironment, we investigated the interaction between tumor hypoxia dynamics and the PD-1/PD-L1 axis in HNSCC patients undergoing chemoradiation and its relevance for patient outcomes in a prospective trial. Methods: 49 patients treated with definitive chemoradiation for locally advanced HNSCC were enrolled in this trial and received longitudinal hypoxia PET imaging using fluorine-18 misonidazole ([18F]FMISO) at weeks 0, 2 and 5 during treatment. Pre-therapeutic tumor biopsies were immunohistochemically analyzed regarding the PD-1/PD-L1 expression both on immune cells and on tumor cells, and potential correlations between the PD-1/PD-L1 axis and tumor hypoxia dynamics during chemoradiation were assessed using Spearman's rank correlations. Hypoxia dynamics during treatment were quantified by subtracting the standardized uptake value (SUV) index at baseline from the SUV values at weeks 2 or 5, whereby SUV index was defined as ratio of maximum tumor [18F]FMISO SUV to mean SUV in the contralateral sternocleidomastoid muscle (i.e. tumor-to-muscle ratio). The impact of the PD-1/PD-L1 expression alone and in combination with persistent tumor hypoxia on locoregional control (LRC), progression-free survival (PFS) and overall survival (OS) was examined using log-rank tests and Cox proportional hazards models. Results: Neither PD-L1 nor PD-1 expression levels on tumor-infiltrating immune cells influenced LRC (HR = 0.734; p = 0.480 for PD-L1, HR = 0.991; p = 0.989 for PD-1), PFS (HR = 0.813; p = 0.597 for PD-L1, HR = 0.796; p = 0.713 for PD-1) or OS (HR = 0.698; p = 0.405 for PD-L1, HR = 0.315; p = 0.265 for PD-1). However, patients with no hypoxia resolution between weeks 0 and 2 and PD-L1 expression on tumor cells, quantified by a tumor proportional score (TPS) of at least 1%, showed significantly worse LRC (HR = 3.374, p = 0.022) and a trend towards reduced PFS (HR = 2.752, p = 0.052). In the multivariate Cox regression analysis, the combination of absent tumor hypoxia resolution and high tumoral PD-L1 expression remained a significant prognosticator for impaired LRC (HR = 3.374, p = 0.022). On the other side, tumoral PD-L1 expression did not compromise the outcomes of patients whose tumor-associated hypoxia declined between week 0 and 2 during chemoradiation (LRC: HR = 1.186, p = 0.772, PFS: HR = 0.846, p = 0.766). Conclusion: In this exploratory analysis, we showed for the first time that patients with both persistent tumor-associated hypoxia during treatment and PD-L1 expression on tumor cells exhibited a worse outcome, while the tumor cells' PD-L1 expression did not influence the outcomes of patients with early tumor hypoxia resolution. While the results have to be validated in an independent cohort, these findings form a foundation to investigate the combination of hypoxic modification and immune checkpoint inhibitors for the unfavorable subgroup, moving forward towards personalized radiation oncology treatment.

Project description:BackgroundA subgroup of patients undergoing TKA is unhappy with the outcome of surgery and preoperative psychological factors may play a role in their dissatisfaction.Questions/purposesWe asked whether (1) psychological factors, as measured by preoperative self-reported questionnaires, predicted poor outcome after TKA, and (2) whether certain psychological factors examined predicted poor outcome better than others.MethodsWe performed a systematic review and meta-analysis of prospective observational studies published in MEDLINE, CINAHL®, EMBASE™, and PsycINFO® databases from their date of inception to October 2013, augmented with a manual search of bibliographies. Study eligibility was performed according to an a priori protocol. Included studies were assessed for quality according to the Newcastle-Ottawa scale. Two reviewers independently performed the search, identified eligible studies, assessed their methodologic quality, and extracted data. Outcomes of interest included postoperative dissatisfaction, pain, or limited function of the patients.ResultsA total of 19 studies (17 cohort studies and two cross-sectional surveys) containing data on 9046 TKAs performed in 8704 adult patients were included in the review. Mean patient age was 68 years and followup ranged from 6 to 60 months (mean study followup, 14 months). Clinical and methodologic heterogeneity in study design prevented the statistical pooling of data and subsequent meta-analysis. Dissatisfaction rates with TKA ranged from 7.5% to 28.3%. Psychological health was deemed a significant predictor of satisfaction, pain, or function at a minimum of 6 months after TKA in 16 studies. The remaining three studies did not find this relationship. Baseline mental health factors may affect patient satisfaction, their long-term perception of pain, and their motivation to return to the desired level of function. We were unable to determine the most relevant psychological states or the most appropriate way to assess them with our systematic review.ConclusionsThe preoperative psychological state of a patient may affect the outcome after a TKA. A comprehensive psychological assessment of patients is required to examine the long-term effect of such psychological factors on the eventual outcomes of TKA once the recovery phase is complete and to assess the effect that treatment for these psychological conditions may have on decreasing the dissatisfaction rate with TKA in this population.

Dataset Information

Prognostic Factors Predict Oncological Outcome in Older Patients With Head and Neck Cancer Undergoing Chemoradiation Treatment.

Purpose

Methods

Results

Conclusion

Publications

Prognostic Factors Predict Oncological Outcome in Older Patients With Head and Neck Cancer Undergoing Chemoradiation Treatment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets