Optimal Cutoff Age for Predicting Mortality Associated with Differentiated Thyroid Cancer.
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ABSTRACT:
SUBMITTER: Kim SJ
PROVIDER: S-EPMC4477980 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveElderly age is one of the poor prognostic factors in epithelial ovarian cancer (EOC), but the optimal age cut-off is not known. The present study sought to identify the ideal age cutoff that represents a negative prognostic factor in EOC, considering the geriatric assessment.MethodsHazard ratios (HRs) with p-values were calculated using all possible age cutoffs with stage, histology, grade, optimality and comorbidities as covariates in multivariate Cox regression model. The trends of p-value and HR by age cutoff were further evaluated in a subgroup of histology and in The Cancer Genome Atlas (TCGA) dataset. In addition, propensity score-matching analysis using the identified age cutoff was performed.ResultsAn age of 66 years was shown to be the most significant cutoff for defining old age with independent prognostic power (HR=1.45; 95% confidence interval=1.04-2.03; p=0.027). This result was also observed with the analyses of serous histology subgroup and with the analysis of a TCGA dataset with serous EOC. In survival analysis, patients aged ?66 years had significantly worse overall survival compared with younger individuals (56 months vs. 87 months; p=0.006), even following propensity score matching (57 vs. 78 months; p=0.038).ConclusionAn age of 66 years is the best cutoff to define elderly age in serous EOC patients considering the geriatric assessment, and this information can be used in the administration of individualized therapies in elderly EOC patients.
| S-EPMC6304408 | biostudies-literature
Project description:BackgroundAge 45 years is used as a cutoff in the staging of well-differentiated thyroid cancer (WDTC) as it represents the median age of most datasets. The aim of this study was to determine a statistically optimized age threshold using a large dataset of patients treated at a comprehensive cancer center.MethodsOverall, 1807 patients with a median follow-up of 109 months were included in the study. Recursive partitioning was used to determine which American Joint Committee on Cancer (AJCC) variables were most predictive of disease-specific death, and whether a different cutoff for age would be found. From the resulting tree, a new age cutoff was picked and patients were restaged using this new cutoff.ResultsThe 10-year disease-specific survival (DSS) by Union for International Cancer Control (AJCC/UICC) stage was 99.6, 100, 96, and 81 % for stages I-IV, respectively. Using recursive partitioning, the presence of distant metastasis was the most powerful predictor of DSS. For M0 patients, age was the next most powerful predictor, with a cutoff of 56 years. For M1 patients, a cutoff at 54 years was most predictive. Having reviewed the analysis, age 55 years was selected as a more robust age cutoff than 45 years. The 10-year DSS by new stage (using age 55 years as the cutoff) was 99.2, 98, 100, and 74 % for stages I-IV, respectively.ConclusionA change in age cutoff in the AJCC/UICC staging for WDTC to 55 years would improve the accuracy of the system and appropriately prevent low-risk patients being overstaged and overtreated.
| S-EPMC4959904 | biostudies-literature
Project description:BackgroundAge at diagnosis (AAD) and telomerase reverse transcriptase (TERT) promoter mutations are prognostic factors in differentiated thyroid carcinoma (DTC), and the prevalence of the mutations increases with AAD. Considering this correlation, we investigated whether an interaction between AAD and the mutations is present and whether the mutation mediates the effect of AAD on the mortality rate in DTC.MethodsThe study included 393 patients with DTC who were followed-up after thyroidectomy at a single medical center in Korea from 1994 to 2004. Multivariable Cox regression was used to investigate the interaction of AAD and TERT promoter mutation. Mediation analysis was conducted using a regression-based causal mediation model.ResultsThe age-associated mortality rate increased progressively in all DTC patients and wild-type TERT group (WT-TERT) with a linear trend (p < 0.001) contrary to mutant TERT group (M-TERT) (p = 0.301). Kaplan-Meier curves declined progressively with increasing AAD in the entire group, but the change was without significance in M-TERT. The effect of AAD on mortality was not significant (adjusted HR: 1.07, 95% CI 0.38-3.05) in M-TERT. An interaction between AAD and TERT promoter mutation (p = 0.005) was found in a multivariable Cox regression. TERT promoter mutations mediated the effect of AAD on the mortality rate by 36% in DTC in a mediation analysis.ConclusionsConsidering the mediation of TERT promoter mutation on the effect of AAD on mortality, inclusion of TERT promoter mutation in a stage classification to achieve further individualized prediction in DTC is necessary.
| S-EPMC10637683 | biostudies-literature
Project description:Radiation is a well-described risk factor for differentiated thyroid carcinoma (DTC). Although the natural history of DTC following nuclear disasters and in healthcare workers with chronic radiation exposure (RE) has been described, little is known about DTC following short-term exposure to therapeutic medical radiation for benign disease. This study compares DTC morphology and outcomes in patients with and without a prior history of therapeutic external RE.A retrospective review was performed of patients with DTC treated at The University of Chicago between 1951 and 1987, with a median follow-up of 27 years (range 0.3-60 years). Patients were classified as either having (RE+) or not having (RE-) a history of therapeutic RE. Variables examined included sex, age at RE, dose of RE, indication for RE, DTC histology, and outcome. Morphology was determined by blinded retrospective review of all available histologic slides. Outcomes were assessed using Cox proportional hazards model and Kaplan-Meier curves.Of 257 DTC patients, 165 (64%) were RE- and 92 (36%) were RE+, with males comprising a greater proportion of the RE+ group (43.5% vs. 27.3%; p?=?0.01). A total of 94.2% of DTC cases were classic papillary cancers; histology did not differ between RE+ and RE- cohorts (p?=?0.73). RE was associated with an increased median overall survival (OS; 43 years vs. 38 years; hazard ratio [HR]?=?0.55 [confidence interval (CI) 0.34-0.89]; p?=?0.01). Survival for males in the RE- group was significantly worse than it was for RE- females (HR?=?1.78 [CI 1.05-3.03]; p?=?0.03) or RE+ males (HR?=?2.98 [CI 1.39-6.38]; p?=?0.01). Recurrence did not differ between the RE+ and RE- groups (HR?=?0.85 [CI 0.52-1.41]; p?=?0.54), nor did DTC-specific mortality (HR?=?0.54 [CI 0.21-1.37]; p?=?0.20).While DTC following RE has historically been considered a more aggressive variant than DTC in the absence of RE, the present data indicate that RE+ DTC is associated with better OS than RE- DTC, especially for males. Additionally, recent reports are confirmed of equivalent rates of thyroid cancer recurrence. These results warrant further investigation into the factors underlying this unexpected finding.
| S-EPMC4976248 | biostudies-literature
Project description:Prognosis in Differentiated Thyroid Cancer (DTC) patients is excellent, but a significant degree of overtreatment still exists because of the inability to accurately identify small patient cohorts who experience a more aggressive form of the disease, often associated with certain poor prognostic factors. Identifying these cohorts at an early stage would allow patients at high risk to receive more aggressive treatment while avoiding unnecessary and invasive treatments in those at low risk. Most risk stratification systems include age, tumor size, grade, presence of local invasion, and regional or distant metastases. Here we discuss these common factors as well as their association with treatment response, but also other upcoming markers including histology and multifocality of primary tumor, dose administered and preparation method for Radioiodine Therapy (RAI), Thyroglobulin (Tg), Anti-thyroglobulin Antibodies (Tg-Ab) levels both at initial management and during follow-up, and the presence of previously existing benign thyroid disease. In addition, we examine the role of remnant size and avidity as well as surgeons' experience in performing thyroidectomies with recurrence rate, discussing its impact on disease prognosis. Our results reveal that treatment response has a statistically significant association with histology, T and M stages, surgeons' experience, Tg levels and remnant score both during RAI and follow up and Tg-Ab levels during follow-up whole body scan (WBS).
| S-EPMC7565378 | biostudies-literature
Project description:BackgroundThe diagnosis of radioiodine refractory differentiated thyroid cancer (RAIR-DTC) is primarily based on clinical evolution and iodine uptake over the lesions, which is still time-consuming, thus urging a predictive model for timely RAIR-DTC informing. The aim of this study was to develop a nomogram model for RAIR prediction among DTC patients with distant metastases (DM).MethodsData were extracted from the treatment and follow-up databases of Peking Union Medical College Hospital between 2010 and 2021. A total of 124 patients were included and divided into RAIR (n=71) and non-RAIR (n=53) according to 2015 ATA guidelines. All patients underwent total thyroidectomy followed by at least two courses of RAI treatment. Serological markers and various clinical, pathological, genetic status, and imaging factors were integrated into this study. The pre-treatment stimulated Tg and pre- and post-treatment suppressed Tg at the first and second course RAI treatment were defined as s-Tg1, s-Tg2, sup-Tg1, and sup-Tg2, respectively. Δs-Tg denoted s-Tg1/s-Tg2, and Δs-TSH denoted s-TSH1/s-TSH2. Multivariate logistic regression and correlation analysis were utilized to determine the independent predictors of RAIR. The performance of the nomogram was assessed by internal validation and receiver operating characteristic (ROC) curve, and benefit in clinical decision-making was assessed using decision curve.ResultsIn univariate logistic regression, nine possible risk factors were related to RAIR. Correlation analysis showed four of the above factors associated with RAIR. Through multivariate logistic regression, Δs-Tg/Δs-TSH<1.50 and age upon diagnosis were obtained to develop a convenient nomogram model for predicting RAIR. The model was internally validated and had good predictive efficacy with an AUC of 0.830, specificity of 0.830, and sensitivity of 0.755. The decision curve also showed that if the model is used for clinical decision-making when the probability threshold is between 0.23 and 0.97, the net benefit of patients is markedly higher than that of the TreatAll and TreatNone control groups.By using 1.50 as a cut-off ofΔs-Tg/Δs-TSH, differing biochemical progression among the generally so-called RAIR can be further stratified as meaningfully rapidly or slowly progressive patients (P=0.012).ConclusionsA convenient user-friendly nomogram model was developed with good predictive efficacy for RAIR. The progression of RAIR can be further stratified as rapidly or slowly progressive by using 1.50 as a cut-off value of Δs-Tg/Δs-TSH.
| S-EPMC9950494 | biostudies-literature
Project description:BackgroundDifferentiated thyroid cancer (DTC) is the most common type of thyroid tumor with a high recurrence rate. Here, we developed a nomogram to effectively predict postoperative disease-free survival (DFS) in DTC patients.MethodsThe mRNA expressions and clinical data of DTC patients were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Seventy percent of patients were randomly selected as the training dataset, and thirty percent of patients were classified into the testing dataset. Multivariate Cox regression analysis was adopted to establish a nomogram to predict 1-year, 3-year, and 5-year DFS rate of DTC patients.ResultsA five-gene signature comprised of TENM1, FN1, APOD, F12, and BTNL8 genes was established to predict the DFS rate of DTC patients. Results from the concordance index (C-index), area under curve (AUC), and calibration curve showed that both the training dataset and the testing dataset exhibited good prediction ability, and they were superior to other traditional models. The risk score and distant metastasis (M) of the five-gene signature were independent risk factors that affected DTC recurrence. A nomogram that could predict 1-year, 3-year, and 5-year DFS rate of DTC patients was established with a C-index of 0.801 (95% CI: 0.736, 0.866).ConclusionOur study developed a prediction model based on the gene expression and clinical characteristics to predict the DFS rate of DTC patients, which may be applied to more accurately assess patient prognosis and individualized treatment.
| S-EPMC8221860 | biostudies-literature
Project description:Age has been included in various prognostic scoring systems for differentiated thyroid cancer (DTC). The aim of this study is to re-examine the relationship between age and prognosis by using Surveillance, Epidemiology, and End Results (SEER) population-based database. We identified 51,061 DTC patients between 2004 and 2012. Patients were separated into 10-year age groups. Cancer cause-specific survival (CSS) and overall survival (OS) data were obtained. Kaplan-Meier and multivariable Cox models were built to analyze the outcomes and risk factors. Increasing age gradient with a 10-year interval was associated with the trend of higher proportions for male gender, grade III/IV and summary stage of distant metastases. Both CSS and OS continued to worsen with increasing age, being poorest in in the oldest age group (≥71); multivariate analysis confirmed that CSS continued to fall with each age decade, significantly starting at 60 years (HR = 7.5, 95% 1.0-54.1, p = 0.047) compared to the young group (≤20). Similarly, multivariate analysis suggested that OS continued worsening with increasing age, but starting at 40 years (HR = 3.7, 95% 1.4-10.1, p = 0.009) compared to the young group. The current study suggests that an age exceeding 60 years itself represents an unfavorable prognostic factor and high risk for cancer-specific death in DTC.
| S-EPMC4897617 | biostudies-literature
Project description:BackgroundMedullary thyroid cancer (MTC) is a rare thyroid cancer accounting for 5 % of all thyroid malignancies. The purpose of our study was to design a predictive nomogram for cancer-specific mortality (CSM) utilizing clinical, pathological, and biochemical variables in patients with MTC.MethodsMTC patients managed entirely at Memorial Sloan-Kettering Cancer Center between 1986 and 2010 were identified. Patient, tumor, and treatment characteristics were recorded, and variables predictive of CSM were identified by univariable analyses. A multivariable competing risk model was then built to predict the 10-year cancer specific mortality of MTC. All predictors of interest were added in the starting full model before selection, including age, gender, pre- and postoperative serum calcitonin, pre- and postoperative CEA, RET mutation status, perivascular invasion, margin status, pathologic T status, pathologic N status, and M status. Stepdown method was used in model selection to choose predictive variables.ResultsOf 249 MTC patients, 22.5 % (56/249) died from MTC, whereas 6.4 % (16/249) died secondary to other causes. Mean follow-up period was 87 ± 67 months. The seven variables with the highest predictive accuracy for cancer specific mortality included age, gender, postoperative calcitonin, perivascular invasion, pathologic T status, pathologic N status, and M status. These variables were used to create the final nomogram. Discrimination from the final nomogram was measured at 0.77 with appropriate calibration.ConclusionsWe describe the first nomogram that estimates cause-specific mortality in individual patients with MTC. This predictive nomogram will facilitate patient counseling in terms of prognosis and subsequent clinical follow up.
| S-EPMC4986610 | biostudies-literature
Project description:BackgroundIn most staging systems, 45 years of age is used to differentiate low risk thyroid cancer from high risk thyroid cancer. However, recent studies have questioned both the precise 45 year age point and the concept of using a binary cut off as accurate predictors of disease specific mortality.MethodsA cohort of 3664 thyroid cancer patients that received surgery and adjuvant treatment at Memorial Sloan Kettering Cancer Center (MSKCC) from the years 1985 to 2010 were analyzed to determine the significance of age at diagnosis as a categorical variable at a variety of age cutoffs (5 year intervals between 30 and 70 years of age). The unadjusted and adjusted hazard ratio for the association between disease-specific survival and age was determined using a Cox proportional hazards model adjusted for other predictive variables sex, histology, and pathological T, N, and M status. Furthermore, predictive nomograms of disease-specific mortality were created and validated on an external dataset of 4551 patients to evaluate the impact of age at diagnosis as both a categorical and continuous variable.ResultsIn the MSKCC cohort, with a median follow-up time of 54 months (range 1-332), there were 59 deaths from thyroid cancer with a 10 year disease-specific survival of 96%. Adjusted hazard ratios for all age cutoffs from age 30 to age 70 years were significant. There was no specific cutoff age which risk stratifies patients with differentiated thyroid cancer (DTC). Categorizing age into five strata (<40, 40-49, 50-59, 60-69 and >70 years) showed a 37-fold increase in hazard ratio from age <40 years to age >70 years. A predictive nomogram using age as a continuous variable with other predictive variables had a high concordance index of 96%. Validation on the external cohort had a concordance index of 73%.ConclusionsMortality from DTC increases progressively with advancing age. There is no specific cutoff age which risk stratifies patients with DTC. A predictive nomogram using age as a continuous variable may be a more appropriate tool for stratifying patients with DTC and for predicting outcome.
| S-EPMC4968282 | biostudies-literature