HNRNPC promotes estrogen receptor-positive breast cancer cell cycle by stabilizing WDR77 mRNA in an m6A-dependent manner.

Breast cancer has become the most commonly diagnosed cancer. Heterogeneous nuclear ribonucleoprotein C (HNRNPC), a reader of N6-methyladenosine (m6A), has been observed to be upregulated in various types of cancer. Nevertheless, the role of HNRNPC in breast cancer and whether it is regulated by m6A modification deserve further investigation. The expression of HNRNPC in breast cancer was examined by quantitative real-time polymerase chain reaction and western blot analysis. RNA immunoprecipitation was performed to validate the binding relationships between HNRNPC and WD repeat domain 77 (WDR77). The effects of HNRNPC and m6A regulators on WDR77 were investigated by actinomycin D assay. The experiments in vivo were conducted in xenograft models. In this research, we found that HNRNPC was highly expressed in breast cancer, and played a crucial role in cell growth, especially in the luminal subtype. HNRNPC could combine and stabilize WDR77 mRNA. WDR77 successively drove the G1/S phase transition in the cell cycle and promoted cell proliferation. Notably, this regulation axis was closely tied to the m6A modification status of WDR77 mRNA. Overall, a critical regulatory mechanism was identified, as well as promising targets for potential treatment strategies for luminal breast cancer.

Causal inference between aggressive extrathyroidal extension and survival in papillary thyroid cancer: a propensity score matching and weighting analysis.

Background: Extrathyroidal extension is a major risk factor for poor prognosis in papillary thyroid cancer. However, the effect of different degrees of extrathyroidal extension on prognosis remains controversial. We performed a retrospective study to elucidate how the extent of extrathyroidal extension in papillary thyroid cancer affected the clinical prognosis of patients and its covariates. Methods: The study included 108,426 patients with papillary thyroid cancer. We categorized the extent of extension into none, capsule, strap muscles, and other organs. Three causal inference methods for retrospective studies, namely, inverse probability of treatment weighting, standardized mortality ratio weighting, and propensity score matching analysis, were used to minimize potential selection bias. Kaplan-Meier analysis and univariate Cox regression analyses were applied to analyze the precise effect of ETE on survival in papillary thyroid cancer patients. Results: In the Kaplan-Meier survival analysis, only extrathyroidal extension into or beyond the strap muscles was statistically significant for both overall survival (OS) and thyroid cancer-specific survival (TCSS). In univariate Cox regression analyses before and after matching or weighting based on causal inference, extrathyroidal extension into soft tissues or other organs is a high-risk factor for both overall survival and thyroid cancer-specific survival. Sensitivity analysis revealed that lower overall survival was observed in patients with older age (≥55) and larger tumor size (>2 cm) of papillary thyroid cancer with extrathyroidal extension into or beyond the strap muscles. Conclusions: Our study indicates that extrathyroidal extension into soft tissues or other organs is a high-risk factor in all papillary thyroid cancer. Even though invasion into the strap muscles did not seem to be a marker for poor prognosis, it still impaired the overall survival of patients with older age (≥55 years old) or larger tumor size (>2 cm). Further investigation is needed to confirm our results and to clarify further risk factors independent of extrathyroidal extension.

Angiography-based coronary flow reserve: The feasibility of automatic computation by artificial intelligence.

BACKGROUND: Coronary flow reserve (CFR) has prognostic value in patients with coronary artery disease. However, its measurement is complex, and automatic methods for CFR computation are scarcely available. We developed an automatic method for CFR computation based on coronary angiography and assessed its feasibility. METHODS: Coronary angiographies from the Corelab database were annotated by experienced analysts. A convolutional neural network (CNN) model was trained for automatic segmentation of the main coronary arteries during contrast injection. The segmentation performance was evaluated using 5-fold cross-validation. Subsequently, the CNN model was implemented into a prototype software package for automatic computation of the CFR (CFRauto) and applied on a different sample of patients with angiographies performed both at rest and during maximal hyperemia, to assess the feasibility of CFRauto and its agreement with the manual computational method based on frame count (CFRmanual). RESULTS: Altogether, 137,126 images of 5913 angiographic runs from 2407 patients were used to develop and evaluate the CNN model. Good segmentation performance was observed. CFRauto was successfully computed in 136 out of 149 vessels (91.3%). The average analysis time to derive CFRauto was 18.1 ± 10.3 s per vessel. Moderate correlation (r = 0.51, p < 0.001) was observed between CFRauto and CFRmanual, with a mean difference of 0.12 ± 0.53. CONCLUSIONS: Automatic computation of the CFR based on coronary angiography is feasible. This method might facilitate wider adoption of coronary physiology in the catheterization laboratory to assess microcirculatory function.

Automatic assessment of collaterals physiology in chronic total occlusions by means of artificial intelligence.

BACKGROUND: Assessment of collaterals physiology in chronic total occlusions (CTO) currently requires dedicated devices, adds complexity, and increases the cost of the intervention. This study sought to derive collaterals physiology from flow velocity changes (ΔV) in donor arteries, calculated with artificial intelligence- aided angiography. METHODS: Angiographies with successful percutaneous coronary intervention (PCI) in 2 centers were retro- spectively analyzed. CTO collaterals were angiographically evaluated according to Rentrop and collateral connections (CC) classifications. Flow velocities in the primary and secondary collateral donor arteries (PCDA, SCDA) were automatically computed pre and post PCI, based on a novel deep-learning model to extract the length/time curve of the coronary filling in angiography. Parameters of collaterals physiology, Δcollateral-flow (Δfcoll) and Δcollateral-flow-index (ΔCFI), were derived from the ΔV pre-post. RESULTS: The analysis was feasible in 105 out of 130 patients. Flow velocity in the PCDA significantly decreased after CTO-PCI, proportionally to the angiographic collateral grading (Rentrop 1: 0.02 ± 0.01 m/s; Rentrop 2: 0.04 ± 0.01 m/s; Rentrop 3: 0.07 ± 0.02 m/s; p < 0.001; CC0: 0.01 ± 0.01 m/s; CC1: 0.04 ± ± 0.02 m/s; CC2: 0.06 ± 0.02 m/s; p < 0.001). Δfcoll and ΔCFI paralleled ΔV. SCDA also showed a greater reduction in flow velocity if its collateral channels were CC1 vs. CC0 (0.03 ± 0.01 vs. 0.01 ± 0.01 m/s; p < 0.001). For each individual patient, ΔV was more pronounced in the PCDA than in the SCDA. CONCLUSIONS: Automatic assessment of collaterals physiology in CTO is feasible, based on a deeplearning model analyzing the filling of the donor vessels in angiography. The changes in collateral flow with this novel method are quantitatively proportional to the angiographic grading of the collaterals.

Immune and Stroma Related Genes in Breast Cancer: A Comprehensive Analysis of Tumor Microenvironment Based on the Cancer Genome Atlas (TCGA) Database.

Background: Tumor microenvironment is essential for breast cancer progression and metastasis. Our study sets out to examine the genes affecting stromal and immune infiltration in breast cancer progression and prognosis. Materials and Methods: This work provides an approach for quantifying stromal and immune scores by using ESTIMATE algorithm based on gene expression matrix of breast cancer patients in TCGA database. We found differentially expressed genes (DEGs) through limma R package. Functional enrichments were accessed through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Besides, we constructed a protein-protein network, identified several hub genes in Cytoscape, and discovered functionally similar genes in GeneMANIA. Hub genes were validated with prognostic data by Kaplan-Meier analysis both in The Cancer Genome Atlas (TCGA) database and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database and a meta-analysis of hub genes prognosis data was utilized in multiple databases. Furthermore, their relationship with infiltrating immune cells was evaluated by Tumor IMmune Estimation Resource (TIMER) web tool. Cox regression was utilized for overall survival (OS) and recurrence-free survival (RFS) in TCGA database and OS in METABRIC database in order to evaluate the impact of stromal and immune scores on patients prognosis. Results: One thousand and eighty-five breast cancer patients were investigated and 480 differentiated expressed genes (DEGs) were found based on the analysis of mRNA expression profiles. Functional analysis of DEGs revealed their potential functions in immune response and extracellular interaction. Protein-protein interaction network gave evidence of 10 hub genes. Some of the hub genes could be used as predictive markers for patients prognosis. In this study, we found that tumor purity and specific immune cells infiltration varied in response to hub genes expression. The multivariate cox regression highlighted the fact that immune score played a detrimental role in overall survival (HR = 0.45, 95% CI: 0.27-0.74, p = 0.002) and recurrence-free survival (HR = 0.41, 95% CI: 0.22-0.77, p = 0.006) in TCGA database. These result was confirmed in METABRIC database that immune score was a protector of OS (HR = 0.88, 95% CI: 0.77-0.99, p = 0.039). Conclusions: Our findings promote a better understanding of the potential genes behind the regulation of tumor microenvironment and cells infiltration. Immune score should be considered as a prognostic factor for patients' survival.

Comprehensive analysis of the association between tumor glycolysis and immune/inflammation function in breast cancer.

BACKGROUND: Metabolic reprogramming, immune evasion and tumor-promoting inflammation are three hallmarks of cancer that provide new perspectives for understanding the biology of cancer. We aimed to figure out the relationship of tumor glycolysis and immune/inflammation function in the context of breast cancer, which is significant for deeper understanding of the biology, treatment and prognosis of breast cancer. METHODS: Using mRNA transcriptome data, tumor-infiltrating lymphocytes (TILs) maps based on digitized H&E-stained images and clinical information of breast cancer from The Cancer Genome Atlas projects (TCGA), we explored the expression and prognostic implications of glycolysis-related genes, as well as the enrichment scores and dual role of different immune/inflammation cells in the tumor microenvironment. The relationship between glycolysis activity and immune/inflammation function was studied by using the differential genes expression analysis, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analyses (GSEA) and correlation analysis. RESULTS: Most glycolysis-related genes had higher expression in breast cancer compared to normal tissue. Higher phosphoglycerate kinase 1 (PGK1) expression was associated with poor prognosis. High glycolysis group had upregulated immune/inflammation-related genes expression, upregulated immune/inflammation pathways especially IL-17 signaling pathway, higher enrichment of multiple immune/inflammation cells such as Th2 cells and macrophages. However, high glycolysis group was associated with lower infiltration of tumor-killing immune cells such as NKT cells and higher immune checkpoints expression such as PD-L1, CTLA4, FOXP3 and IDO1. CONCLUSIONS: In conclusion, the enhanced glycolysis activity of breast cancer was associated with pro-tumor immunity. The interaction between tumor glycolysis and immune/inflammation function may be mediated through IL-17 signaling pathway.

Columnar cell papillary thyroid carcinoma prognosis: findings from the SEER database using propensity score matching analysis.

BACKGROUND: Columnar cell papillary thyroid carcinoma (CCPTC) is a rare variant of papillary thyroid carcinoma (PTC), whose prognosis, as defined by the American Thyroid Association (ATA) guidelines, is considered poor, although available evidence is insufficient for reliable assessment. This study aimed to investigate the CCPTC prognosis using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Data of thyroid cancer patients, recorded from 2004 to 2013, were extracted to assess the CCPTC prognosis. All-cause and cancer-specific mortality rates associated with thyroid cancer types were evaluated using the Kaplan-Meier method and Cox proportional hazards regression. Propensity score matching analysis was used to adjust for potential confounders. RESULTS: Cancer-specific mortality per 1000 person-years was higher for CCPTC than for classic papillary thyroid cancer (CPTC) and follicular thyroid cancer (FTC). The multivariate Cox regression model revealed that the cancer-specific and all-cause mortality rates were higher for CCPTC than for CPTC but not FTC. However, propensity score matching analysis demonstrated a significantly lower survival for CCPTC than for both CPTC and FTC. CONCLUSIONS: Our findings provide evidence to support the poor prognosis associated with CCPTC. These findings may serve to improve the diagnosis of CCPTC, provide reliable reference data for clinical use, and increase the comprehensiveness of current guidelines.

Small Cell Carcinoma: a Rare Subtype of Thyroid Cancer with Unanticipated Prognosis.

The prognosis of small cell thyroid carcinoma (SCTC) in a large cohort has not been well reported in the literature. In this study, we analyzed the mortality of SCTC, in comparison to medullary thyroid cancer (MTC) and anaplastic thyroid cancer (ATC), based on the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute, to determine the prognosis of SCTC. Information regarding patients with a diagnosis of MTC, ATC, or SCTC, between 2004 and 2013, was acquired from the SEER database. Patient survival curves were assessed by Cox proportional hazards regression analyses, Kaplan-Meier analyses, and log-rank tests. In a Kaplan-Meier analysis of the entire cohort of thyroid cancer patients, cancer-specific survival declined sharply for patients with SCTC, but it declined more modestly for patients with MTC. The cancer-specific survival was not significantly different between SCTC and ATC. Unadjusted Cox regression analysis showed that SCTC had a higher cancer-specific mortality than MTC but a similar prognosis as ATC. SCTC showed a higher cancer-specific mortality than MTC and ATC after adjustments for various confounding factors. SCTC was found to have a more highly lethal clinical course than MTC and had a similar death rate to ATC. Therefore, we recommend that aggressive, radical treatment like surgery or radiation should be performed for these patients.

Automatic coronary blood flow computation: validation in quantitative flow ratio from coronary angiography.

To assess a novel approach for automatic flow velocity computation in deriving quantitative flow ratio (QFR) from coronary angiography. QFR is a novel approach for assessment of functional significance of coronary artery stenosis without using pressure wire and induced hyperemia. Patient-specific coronary flow is estimated semi-automatically by frame count method, which is subjective and inconvenient in the workflow of QFR analysis. The vascular structures were automatically delineated from coronary angiogram. Subsequently, the centerline of the interrogated vessel was extracted from the delineated lumen on each image frame and the change in the length of centerline was used to compute the flow velocity, which provided patient-specific flow for computation of QFR (QFRauto). A parameter derived from the increase in centerline length was used to automatically quantify the stability of contrast flow. From the two angiographic image runs used for three-dimensional angiographic reconstruction, the one with better stability was used to compute QFRauto. QFRauto was assessed in all patients enrolled in the FAVOR II China study, and compared with the commercialized QFR computational method based on frame count (QFRcount), using pressure wire-based fractional flow reserve (FFR) as the reference standard. Out of 328 vessels with paired FFR data, QFRauto was successfully computed on 325 (99%) vessels with acceptable stability in filling of contrast flow. The flow velocity computed by the proposed approach had a weak to moderate correlation with the frame count method (r = 0.37, p < 0.001), with mean differences of - 0.02 ± 0.07 m/s (p < 0.001). QFRauto had good correlation (r = 0.96, p < 0.001) and agreement (mean difference: - 0.01 ± 0.04, p < 0.001) with QFRcount. Good correlation (r = 0.83, p < 0.001) and agreement (mean difference: 0.01 ± 0.06, p = 0.016) were also observed between QFRauto and FFR. Using FFR ≤ 0.80 to define functional significance of coronary stenosis, the overall diagnostic accuracy for QFRauto was 93.2% (95% CI 90.5-96.0%). The area under the receiver-operating characteristic curve did not differ significantly between QFRcount and QFRauto (difference: 0.00; 95% CI - 0.01 to 0.01; p = 0.529). Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for QFRauto were 92.4% (95% CI 86.0-96.5%), 93.7% (95% CI 89.5-96.6%), 14.7 (95% CI 8.7-25.0), and 0.1 (95% CI 0.0-0.2), respectively. Automatic computation of patient-specific coronary flow velocity based on coronary angiography is feasible. Assessment of QFR based on this novel approach had good diagnostic accuracy in determining the functional significance of coronary stenosis.

YY1-regulated LINC00152 promotes triple negative breast cancer progression by affecting on stability of PTEN protein.

Thousands of lncRNAs have been identified but few have been functionally characterized in triple negative breast cancer (TNBC). LINC00152 was known as cytoskeleton regulator RNA (CYTOR) and expressed in various cancers including breast cancer. But the underlying molecular mechanism of LINC00152 in pathogenesis of TNBC have not been elucidated. In our study, we identified that LINC00152 expression was dramatically elevated in TNBC tissue and cells. Inhibition or overexpression of LINC00152 obviously increased or suppressed PTEN protein expression but did not affect the mRNA expression level. Our further experiments showed up-regulated LINC00152 in TNBC obviously enhanced NEDD4-1 mediated ubiquitination and degradation of PTEN protein. Finally, we demonstrated that YY1 bound with LINC00152 promotor and mostly inhibited the transcription of LINC00152. Furthermore, analysis of clinical samples resource retrieved from databases suggested high LINC00152 expression was correlated with ER or PR negative expression, late TNM stage and lymphatic invasion, as well as shorter overall survival time in patients. Consequently, this study firstly reveals that up-regulated LINC00152 mediates PTEN protein stability attenuation in TNBC.

Prognosis of a rare subtype of thyroid cancer: Spindle cell thyroid carcinoma.

Systemic illustrations of spindle cell thyroid cancer (SCTC), based on a large cohort, are few. We investigated the prognosis of SCTC compared to the most common subtypes, papillary thyroid cancer (PTC) and follicular thyroid cancer (FTC).Information of patients with a diagnosis of SCTC, PTC, or FTC, between 2004 and 2013, was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Patient survival curves were investigated using Kaplan-Meier analyses, log-rank tests, and Cox proportional hazards regression analyses.In a Kaplan-Meier analysis of the entire cohort of thyroid cancer patients, cancer specific survival declined sharply for patients with SCTC, but declined more modestly for patients with PTC and FTC. Unadjusted Cox regression analysis and Kaplan-Meier curve analysis showed that SCTC had a poorer cancer-specific mortality and all-cause mortality compared to PTC and FTC. Similar results were obtained after adjustment for different confounding factors.Our study assessed the prognosis of SCTC, based on a large cohort, compared to PTC and FTC, and found relatively accurate hazard ratios of death rate in SCTC as compared to PTC and FTC. Thus, our findings would provide beneficial insights on patients with SCTC, and aid in treatment decision making, more radical treatment like total-thyoridectomy and/or plus central lymph node dissection should be performed for patients with SCTC.

Prognosis of patients with TX stage differentiated thyroid cancer: propensity scored matching analysis of the SEER database 2004-2013.

In differentiated thyroid cancer (DTC), TX stage is defined as 'primary tumour cannot be assessed'. The prognosis of patients with TX stage remains unclear. The aim of this study was to investigate the prognosis of TX stage and provide a perspective on treatment guidelines. We investigated a large cohort of DTC patients from the Surveillance, Epidemiology, and End Results database between 2004 and 2013. Patient mortality was examined by Kaplan-Meier analyses with log-rank tests and Cox proportional hazards regression analyses. The rate of cancer-specific mortality per 1000 person-years for patients with TX stage was higher than for patients with T1-T3 stage, but lower than for patients with T4 stage. The all-cause mortality per 1000 person-years for TX stage patients was also higher than for T1-T3 stage patients, but lower than for T4 stage patients. TX stage showed significant risk for cancer-specific mortality compared to T1 and T4 stages, but not T2 and T3 stages, after adjusting for influential risk factors. TX stage patients showed no significant risk for all-cause mortality compared to T2-T3 stage patients, but were different than T1 and T4 stage patients. These results provide new implications for the treatment of TX stage DTC patients.

Is biopsy enough for papillary thyroid microcarcinoma?: An analysis of the SEER database 2004 to 2013 with propensity score matching.

The treatment of papillary thyroid microcarcinoma (PTMC) remains deeply controversial. In this study, we investigated the prognosis of patients who underwent biopsy alone, as compared with other forms of thyroidectomy approaches. We sought to provide reference information for treatment selection in cases of PTMC.The analysis included a large cohort of 34,972 PTMC patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2013. Survival was examined by Kaplan-Meier analyses with log-rank tests, Cox proportional-hazards regression analyses, and propensity score matching analyses.In the study cohort, the rate of cancer-specific mortality per 1000 person-years was higher for patients who underwent biopsy alone than for those who underwent other surgical approaches. According to multivariate Cox regression analyses, patients undergoing biopsy had similar cancer-specific survival rates and higher all-cause survival rates in comparison with patients undergoing other surgical approaches. After matching for influential factors using propensity scores, Kaplan-Meier analyses also showed that patients undergoing biopsy had similar cancer-specific survival rates and lower all-cause survival rates in comparison with patients undergoing other surgical approaches.Our results provided helpful implications for the treatment of patients with PTMC.

Correction: Mixed subtype thyroid cancer: A surveillance, epidemiology, and end results database analysis.

[This corrects the article DOI: 10.18632/oncotarget.21242.].

Correction: Propensity score matching analysis of the prognosis for the rare oxyphilic subtype of thyroid cancer (Hurthle cell carcinoma).

[This corrects the article DOI: 10.18632/oncotarget.20732.].

Correction: Unanticipated prognosis of differential thyroid cancer patients with T0 stage: analysis of the SEER database 2004-2013.

[This corrects the article DOI: 10.18632/oncotarget.19988.].

The prognosis of NX stage differentiated thyroid cancer based on propensity score matching and SEER data.

Few studies have evaluated the prognosis or treatment of patients with differentiated thyroid cancer (DTC) according to their NX status. This study investigated this issue to provide a new perspective regarding the treatment guidelines for these patients. Data from 92,447 patients with DTC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2013). Survival outcomes were evaluated using Kaplan-Meier analyses with the log-rank test and Cox proportional hazards regression analysis. The rates of cancer-specific mortality and all-cause mortality (per 1,000 person-years) were significantly higher for patients with NX disease, compared to patients with N0 or N1 disease. Multivariate Cox regression modeling revealed that NX stage was an independent risk factor for cancer-specific mortality compared to N1 stage, but not to N0 stage. Similar results were observed for all-cause mortality. After adjustment using propensity score matching, the cancer-specific and all-cause mortality rates were lower for NX stage compared to N0 stage, whereas no significant difference was observed when comparing the NX stage and N1 stage groups. The unexpectedly poor prognosis of patients with NX stage DTC provides new information that may be relevant for treating these patients.

Propensity score matching analysis of the prognosis for the rare oxyphilic subtype of thyroid cancer (Hurthle cell carcinoma).

There is controversy regarding the prognosis of patients with oxyphilic thyroid cancer (OXTC). The present study compared the prognoses of OXTC, papillary thyroid cancer (PTC), and follicular thyroid cancer (FTC), in order to provide a new perspective regarding the treatment guidelines for these diseases. We evaluated data from patients with thyroid cancer who were included in the Surveillance, Epidemiology, and End Results database between 2004 and 2013. Patient mortality was evaluated using Cox proportional hazards regression analyses and Kaplan-Meier analyses with log-rank tests. The multivariate Cox regression analysis revealed that the cancer-specific survival rate for OXTC was similar to that for PTC, but higher than that for FTC. However, after propensity score matching for relevant factors, the cancer-specific survival rate for OXTC was higher than that for PTC and FTC. This unexpected result provides new implications for the treatment of patients with OXTC.

Propensity score matching analysis of the prognosis for the rare insular subtype of thyroid cancer based on SEER database.

Insular thyroid carcinoma (ITC) is an uncommon thyroid malignancy with an unclear prognosis. The aim of this study was to determine the prognoses of patients with ITC. We investigated a large cohort of patients with differentiated thyroid cancer from the Surveillance, Epidemiology, and End Results (SEER) database who were registered between 2004 and 2013, and compared the prognosis of patients with ITC to those with classic papillary thyroid cancer (CPTC) and follicular thyroid cancer (FTC). Patient mortality was determined using Kaplan-Meier analyses with log-rank tests, as well as Cox proportional hazards regression analyses. The study cohort comprised of 165 patients with ITC, 5419 patients with FTC, and 60739 patients with CPTC. The rate of cancer-specific mortality per 1000 person-years for ITC was higher than that for CPTC or FTC. According to multivariate Cox regression analysis, however, the cancer-specific and all-cause mortality rates of ITC were similar to those of CPTC and FTC. The cancer-specific survival rate in patients with ITC was higher than that in patients with CPTC, but similar to that in patients with FTC, after adjusting for potentially influencing factors using propensity score matching analysis. These findings, which contrast with previously published data, provide new implications for the treatment of patients with ITC.

Do patients with oxyphilic cell papillary thyroid carcinoma have a poor prognosis? Analysis of the surveillance, epidemiology, and end results database 2004-2013 with propensity score matching.

The prognosis of oxyphilic cell papillary thyroid carcinoma (OCPTC) remains unclear. The aim of this study was to investigate the prognosis of OCPTC and provide a new perspective on treatment guidelines for these patients. We investigated a large cohort of DTC patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2013. Patient mortality was examined by Kaplan-Meier analyses with log-rank tests and Cox proportional hazards regression analyses. In the study cohort, the rate of cancer-specific mortality per 1000 person-years for OCPTC was lower than that for classic papillary thyroid cancer (CPTC) and follicular thyroid cancer (FTC). According to the multivariate Cox regression model, the cancer-specific and all-cause mortality rates of OCPTC were similar to that of CPTC and FTC. The cancer-specific survival rate in patients with OCPTC was higher than that in patients with FTC, but similar to patients with CPTC, after matching for influential factors using propensity score matching analysis. The unanticipated prognosis provided new implications for the treatment of patients with OCPTC.