A nomogram to predict postresection 5-year overall survival for patients with uterine leiomyosarcoma

Neoadjuvant or Adjuvant Chemotherapy in Soft-Tissue Sarcoma?

PURPOSE OF REVIEW

The review compares the effectiveness of neoadjuvant(pre-operative, NAC) and adjuvant(post-operative, AC) in Soft Tissue Sarcomas as this topic is controvesial and multiple new studies have been over the years.

RECENT FINDINGS

Sarculator and other nomograms assess patients with a predicted 10-year OS below 60% who will benefit from perioperative chemotherapy. Further research supports perioperative chemotherapy's role. European guidelines do not recommend anthracycline and ifosfamide (AI) perioperative chemotherapy as a standard treatment for STS of the extremities and trunk. However, some studies show that AI chemotherapy can improve recurrence-free survival (RFS). The EORTC 62,771 trial found that the CYVADIC regimen (doxorubicin, dacarbazine, cyclophosphamide, vincristine) reduced RFS without affecting OS. Meanwhile, the EORTC 62,931 trial showed no effect of AI chemotherapy on RFS or OS, but a pooled analysis suggested an OS benefit for patients with R1 (microscopically positive) resections. The AI regimen shows further support from Sarculator-based data, with EORTC 62,931 analysis indicating an improvement in disease-free survival and OS in patients with low expected OS. Similar outcomes were seen in the ISG-STS 1001 study. Recently, PERSARC analysis revealed that AI chemotherapy significantly improves OS in high-grade STS patients with a low 5-year OS prediction (< 33%). NAC improves the chances of complete tumour removal, especially in large, high-grade tumours. It often reduces the need for more aggressive surgeries by shrinking tumours before surgery, leading to higher rates of successful resections with clear margins (R0). Sarculator and other nomograms assess patients with a predicted 10-year OS below 60% who will benefit from perioperative chemotherapy. Further research supports perioperative chemotherapy's role.

Establishment and validation of a nomogram to predict overall survival for patients with primary renal neuroendocrine tumor

Our study aimed to develop a nomogram to predict overall survival (OS) at 1, 3, and 5 years for patients with primary renal neuroendocrine tumor (PRNET). The Surveillance, Epidemiology, and End Results database (2000-2021) was utilized to gather cases and extract data. We performed a multivariate analysis using a Cox proportional-hazards model to identify prognostic factors independently affecting OS. Based on these predictors, a nomogram was constructed and validated internally via a bootstrap resampling method. Finally, we included 266 PRNET patients. The multivariate analysis demonstrated that age, Fuhrman grade, surgery, summary stage, N stage, and histology were prognostic factors independently affecting OS (all P < 0.05). A nomogram was then constructed using the abovementioned predictors, except for the N stage. The bootstrap-corrected concordance index (C-index) of the nomogram was 0.820 (95% CI 0.805-0.835), surpassing the C-index of the TNM stage (0.571, 95% CI 0.550-0.592, P < 0.001). Based on time-dependent C-index results, the nomogram demonstrated a better discriminative ability compared to the TNM staging system. There was a good consistency between the observed values and predicted probabilities indicated by the calibration curves. The nomogram's clinical utility was supported by the decision curve analysis. Additionally, the nomogram can classify PRNET patients into low-risk and high-risk subgroups, with high-risk patients having poorer OS (P < 0.0001). The prognostic nomogram, based on individualized clinicopathological information, may be helpful in predicting survival outcomes for PRNET patients more accurately. Further external validation is required in future studies to confirm our developed nomogram's prognostic accuracy and clinical applicability.

Risk Stratification of Uterine Smooth Muscle Tumors: The Role of Morphology, Immunohistochemistry, and Molecular Testing

Uterine smooth muscle neoplasms are a biologically and clinically heterogeneous group of tumors. Morphology is the cornerstone of pathologic diagnosis of these tumors, and most are readily classified as benign or malignant on the basis of routine histologic examination. However, rare subsets-including intravenous leiomyomatosis, benign metastasizing leiomyoma, and disseminated peritoneal leiomyomatosis-have a capacity for extrauterine spread despite benign cytomorphology. A further subset of uterine smooth muscle neoplasms, termed "smooth muscle tumor of uncertain malignant potential (STUMP)," are not readily classified as benign or malignant and carry an intermediate prognosis. STUMP is a protean category, whose precise definition is subject to disagreement among experts. The risk profiles of different STUMP morphotypes remain largely unresolved. Finally, multiple morphology-based systems for risk stratification of uterine leiomyosarcoma have been proposed, though none is widely adopted. Immunohistochemical and molecular prognostic markers for both STUMP and leiomyosarcoma remain in the early phases of adoption in routine diagnostic practice.

A clinical ultrasound algorithm to identify uterine sarcoma and smooth muscle tumors of uncertain malignant potential in patients with myometrial lesions: the MYometrial Lesion UltrasouNd And mRi study

BACKGROUND

Differential diagnosis between benign uterine smooth muscle tumors and malignant counterpart is challenging.

OBJECTIVE

To evaluate the accuracy of a clinical and ultrasound based algorithm in predicting mesenchymal uterine malignancies, including smooth muscle tumors of uncertain malignant potential.

STUDY DESIGN

We report the 12-month follow-up of an observational, prospective, single-center study that included women with at least 1 myometrial lesion ≥3 cm on ultrasound examination. These patients were classified according to a 3-class diagnostic algorithm, using symptoms and ultrasound features. "White" patients underwent annual telephone follow-up for 2 years, "Green" patients underwent a clinical and ultrasound follow-up at 6, 12, and 24 months and "Orange" patients underwent surgery. We further developed a risk class system to stratify the malignancy risk.

RESULTS

Two thousand two hundred sixty-eight women were included and target lesion was classified as benign in 2158 (95.1%), as other malignancies in 58 (2.6%) an as mesenchymal uterine malignancies in 52 (2.3%) patients. At multivariable analysis, age (odds ratio 1.05 [95% confidence interval 1.03-1.07]), tumor diameter >8 cm (odds ratio 5.92 [95% confidence interval 2.87-12.24]), irregular margins (odds ratio 2.34 [95% confidence interval 1.09-4.98]), color score=4 (odds ratio 2.73 [95% confidence interval 1.28-5.82]), were identified as independent risk factors for malignancies, whereas acoustic shadow resulted in an independent protective factor (odds ratio 0.39 [95% confidence interval 0.19-0.82[). The model, which included age as a continuous variable and lesion diameter as a dichotomized variable (cut-off 81 mm), provided the best area under the curve (0.87 [95% confidence interval 0.82-0.91]). A risk class system was developed, and patients were classified as low-risk (predictive model value <0.39%: 0/606 malignancies, risk 0%), intermediate risk (predictive model value 0.40%-2.2%: 9/1093 malignancies, risk 0.8%), high risk (predictive model value ≥2.3%: 43/566 malignancies, risk 7.6%).

CONCLUSION

The preoperative 3-class diagnostic algorithm and risk class system can stratify women according to risk of malignancy. Our findings, if confirmed in a multicenter study, will permit differentiation between benign and mesenchymal uterine malignancies allowing a personalized clinical approach.

Adjuvant therapy de-escalation for stage I uterine leiomyosarcoma: A systematic review and meta-analysis

OBJECTIVE

To examine the association between adjuvant chemotherapy and survival outcomes in patients with stage I uterine leiomyosarcoma (uLMS).

METHODS

This comprehensive systematic review and meta-analysis through December 31, 2023 (PROSPERO registration number: CRD42024504776) investigated studies that examined survival outcomes in patients with stage I uLMS using 4 public search engines (PubMed, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials). Two investigators searched the studies independently, and survival outcomes (overall survival [OS] and disease-free survival [DFS]) were compared between the adjuvant chemotherapy and observation groups. Utilization rate of adjuvant chemotherapy and the regimens used were also assessed. Kaplan-Meier survival curves in the two treatment groups were evaluated using ImageJ software.

RESULTS

From 1988 to 2022, 16 eligible studies including a total of 5690 patients met the inclusion criteria and evaluated the effect of adjuvant chemotherapy on survival outcomes in patients with stage I uLMS. Adjuvant chemotherapy was utilized in 38.5 % of patients (range, 14.8 % to 70.0 %). Eight studies from 2017 to 2022 compared the survival outcomes between adjuvant chemotherapy and observation. OS was comparable between the two groups in both unadjusted (n = 6, hazard ratio [HR] 1.02, 95 % confidence interval [CI] 0.77-1.35, P = 0.88) and adjusted (n = 4, HR 0.90, 95 %CI 0.56-1.43, P = 0.65) pooled analyses. DFS was also similar between adjuvant chemotherapy and observation in both unadjusted (n = 4, HR 0.78, 95 %CI 0.53-1.13, P = 0.18) and adjusted (n = 2, HR 1.14, 95 %CI 0.67-1.94, P = 0.64) pooled analyses. Adjuvant chemotherapy regimens utilized included doxorubicin, ifosfamide, cisplatin, gemcitabine, and docetaxel as monotherapies or combination therapies.

CONCLUSIONS

In this contemporaneous systematic review and meta-analysis, less than 40 % of patients received adjuvant chemotherapy for stage I uLMS and adjuvant chemotherapy which was not associated with improved survival. These results support the current National Comprehensive Cancer Network clinical practice guidelines that recommends de-escalating adjuvant chemotherapy in stage I uLMS after complete resection.

Individualized evaluation of risk and prognosis in uterine leiomyosarcoma patients with synchronous distant metastases: a real-world retrospective study

Background

Uterine leiomyosarcoma (uLMS) accounts for roughly 70% of all uterine sarcomas, with recurrence and mortality rates notably higher than those of other uterine tumors. The prognosis of uLMS patients who have distant metastases remains poor. The objective of this study was to determine independent risk variables related to distant metastases in patients with uLMS and prognostic factors for those with distant metastases. Subsequently, two practical nomograms were developed and validated to assess the probability of distant metastases and predict survival outcomes for these with distant metastases, respectively.

Methods

A real-world retrospective study was carried out using data from patients diagnosed with primary uLMS in the Surveillance, Epidemiology, and End Results (SEER) database spanning the years 2010 to 2015. Univariate and multivariate logistic regression analyses were utilized to identify clinicopathological characteristics related to the risk of distant metastases, while univariate and multivariate Cox regressions were employed to determine prognostic factors. Then, a risk nomogram incorporating independent risk variables and a prognostic nomogram integrating independent prognostic factors were established in the training cohort and validated for accuracy in the validation cohort, respectively. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and calibration curves were utilized to measure the accuracy of nomograms, while decision curve analysis (DCA) curves were employed to assess their clinical benefit capacity. Based on the median total point derived from the prognostic nomogram, patients were stratified into high- and low-risk groups. The differentiation ability of the prognostic nomogram was evaluated using Kaplan-Meier survival analysis with the log-rank test.

Results

The study encompassed 1,362 patients diagnosed with uLMS, among whom 337 cases (24.7%) manifested synchronous distant metastases at the initial diagnosis. Univariate and multivariate logistic regression analyses identified race, histological grade, T stage, N stage, tumor size, surgery, and chemotherapy as independent risk factors for distant metastases in uLMS patients. The outcomes of both univariate and multivariate Cox analyses indicated that surgery and chemotherapy emerged as independent protective factors for prognosis in uLMS patients with distant metastases, whereas higher histological grade and T stage were identified as independent risk factors. The risk nomogram incorporating independent risk variables and the prognostic nomogram integrating independent prognostic factors could respectively predict the risk of metastases and the prognosis very effectively in both training and validation cohorts.

Conclusions

In summary, we developed the novel well-validated risk nomogram to precisely assess the probability of metastases in uLMS patients and prognostic nomogram to predict the prognosis of those with distant metastases, providing decision-making guidance for tailoring individualized clinical management of these patients.

Comprehensive Review of Uterine Leiomyosarcoma: Pathogenesis, Diagnosis, Prognosis, and Targeted Therapy

Uterine leiomyosarcoma (uLMS) is the most common subtype of uterine sarcomas. They have a poor prognosis with high rates of recurrence and metastasis. The five-year survival for uLMS patients is between 25 and 76%, with survival rates approaching 10-15% for patients with metastatic disease at the initial diagnosis. Accumulating evidence suggests that several biological pathways are involved in uLMS pathogenesis. Notably, drugs that block abnormal functions of these pathways remarkably improve survival in uLMS patients. However, due to chemotherapy resistance, there remains a need for novel drugs that can target these pathways effectively. In this review article, we provide an overview of the recent progress in ascertaining the biological functions and regulatory mechanisms in uLMS from the perspective of aberrant biological pathways, including DNA repair, immune checkpoint blockade, protein kinase and intracellular signaling pathways, and the hedgehog pathway. We review the emerging role of epigenetics and epitranscriptome in the pathogenesis of uLMS. In addition, we discuss serum markers, artificial intelligence (AI) combined with machine learning, shear wave elastography, current management and medical treatment options, and ongoing clinical trials for patients with uLMS. Comprehensive, integrated, and deeper insights into the pathobiology and underlying molecular mechanisms of uLMS will help develop novel strategies to treat patients with this aggressive tumor.

Extremity and Truncal Soft Tissue Sarcoma: Risk Assessment and Multidisciplinary Management

Extremity and truncal soft tissue sarcomas are a heterogeneous group of rare cancers that arise from mesenchymal tissues. Hence, the adoption of tailored risk assessment and prognostication tools plays a crucial role in optimizing the decision-making for which of the many possible treatment strategies to select. Management of these tumors requires a multidisciplinary strategy, which has seen significant development in recent decades. Surgery has emerged as the primary treatment approach, with the main goal of achieving microscopic negative tumor margins. To reduce the likelihood of local recurrence, loco-regional treatments such as radiation therapy and isolated limb perfusion are often added to the treatment regimen in combination with surgery. This approach also enables surgeons to perform limb-sparing surgery, particularly in cases where a positive tumor margin is expected. Chemotherapy may also provide a further benefit in decreasing the probability of local recurrence or reducing distant metastasis in selected patients. Selecting the optimal treatment strategy for these rare tumors is best accomplished by an experienced multi-disciplinary team.

Treatment patterns and outcomes for primary uterine leiomyosarcoma with synchronous isolated lung metastases: A National Cancer Database study of primary resection and metastasectomy

Background

One third of patients with uterine leiomyosarcomas (uLMS) present with distant metastases. Current guidelines do not include recommendations around surgery for metastatic uLMS. Patients with distant metastases commonly receive primary tumor resection for symptoms and so oncologic outcomes after surgery warrant exploration. We describe treatment patterns and outcomes for uLMS patients with synchronous isolated lung metastases (SILM).

Methods

This retrospective analysis of the National Cancer Database identified patients with uLMS and SILM. Patients with non-pulmonary metastases were excluded. We collected demographic, disease, and treatment characteristics and assessed clinicopathologic factors associated with the receipt of surgery on multivariate regression. Median, 1-year, and 5-year overall survival (OS) across treatment approaches were compared using Kaplan-Meier curves and log-rank tests. Multivariate Cox proportional hazard regressions identified independent predictors of survival.

Results

We identified 905 patients with uLMS and SILM between 2004 and 2017. 600 patients had primary tumor resection; 63 also had curative intent surgery with metastasectomy. Patients who did not receive chemotherapy were older (p<0.01) with a higher comorbidity index (p<0.05). Women with private health insurance were more likely to receive chemotherapy (p<0.01) and primary tumor resection (p<0.01). Patients who underwent curative intent surgery had 1-year OS of 71.2% and 5-year survival of 18% compared to 1-year survival of 35.6 % and 5-year survival of 5.16 % for patients who had no surgery. Black women had poorer survival on multivariate regression.

Conclusions

Primary tumor resection and curative intent surgery are associated with improved OS in uLMS with SILM and may be a reasonable treatment option in appropriately selected patients.

Prognostic value of mitotic count in leiomyosarcoma: A comprehensive monocentric retrospective study

BACKGROUND

Leiomyosarcomas (LMSs) include heterogeneous entities with different clinical courses not entirely predicted by known prognostic factors. In particular, the value of mitotic count as independent prognostic factor in LMS has been poorly investigated.

METHODS

We retrospectively analyzed all patients with a diagnosis of LMS who accessed to our Institution from June 1999 to May 2022 for which mitotic count was numerically expressed within the pathology report. Univariate and multivariate analyses were conducted to explore the prognostic value of mitotic count along with other clinical and histological variables.

RESULTS

We identified 121 eligible patients, with a median follow-up of 91.03 months (range 0.62-275.2 months). Median progression-free survival (mPFS) was 16.7 months, and median overall survival (mOS) was 105.6 months. In univariate analysis, mitotic count showed a significant impact on PFS and OS, with an hazard ratio per mitotic unit of 1.03 (1.01-1.04, p < 0.001) and 1.03 (1.01-1.04, p = 0.007), respectively. Similar results were found for locally advanced and metastatic patients, separately. Other significant prognostic factors for PFS were stage at diagnosis, performance status, tumor size and Ki-67, while differentiation, necrosis, grade, stage at diagnosis, tumor size, performance status and age at diagnosis were identified for OS. In multivariate analysis, the only significant factors were mitotic count and the presence of metastases at diagnosis for PFS, whereas the same two factors plus age at diagnosis were identified for OS.

CONCLUSION

Mitotic count represented the most important histological prognostic factor for OS and PFS in localized and metastatic LMS.

Role of radiotherapy in the management of rare gynaecological cancers

There are a large number of gynaecological cancers with rare histologies, for which the available data are limited and usually retrospective. Because of their rarity and poor prognosis, the management of these cancers must be centralized in expert centres, for both histological diagnosis and treatment. With the exception of sarcomas, most endometrial or cervical cancers with rare histologies respond to the same radiation treatment modalities than cancers with more common histologies, although there are some specificities regarding treatments such as neuroendocrine carcinomas (chemotherapy with platinum and etoposide, major role of surgery). For localized or locally advanced ovarian cancer, external beam radiotherapy has a role in the management of hypercalcaemic small cell carcinoma of the ovary. This article summarizes the current role of external beam radiotherapy and brachytherapy in the management of cancers of the uterine cervix, uterine corpus and ovaries, with rare or very rare histologies, and with localized or locally advanced stages.

Low-Grade Uterine Leiomyosarcoma Is Highly Sensitive to Hormonal Treatment

PURPOSE

According to the World Health Organization classification system, uterine leiomyosarcomas (ULMS) are high-grade. A diagnosis of smooth-muscle tumors of uncertain malignant potential (STUMP) is made when Stanford Criteria for ULMS are not met. When a STUMP recurs, the tumor is diagnosed as ULMS and medical treatment is the same as for ULMS. In recent years, some sarcoma centers valued the less aggressive clinical behavior of several recurring STUMP and, given their expression of estrogen and progesterone receptors, started to treat them with hormonal therapy.

EXPERIMENTAL DESIGN

This was a retrospective cohort analysis conducted at three referral centers joining the Leiomyosarcoma Foundation Roundtable. We selected all cases of uterine smooth muscle tumors consistent with STUMP and treated with hormonal therapy.

RESULTS

27 consecutive patients were identified. Median age at diagnosis was 43 years. Stage was IA-IB in more than 70% of patients. In these patients, median time to relapse was 62 months. Sites of first relapses were mostly pelvis and peritoneum (76%). After a median follow-up of 49 months, 14 patients (52%) had a partial response while 10 (37%) had a minor response or stable disease. Median time to progression was not reached.

CONCLUSIONS

We observed a response or long-term stability rate on hormonal therapy in the 90% range; in all cases the time to relapse was significantly longer than in ULMS and in most cases the relapse was abdominal. On the basis of these findings, we conclude that a proportion of patients with uterine smooth muscle neoplasms actually present with a "low-grade ULMS."

A web-based nomogram to predict overall survival for postresection leiomyosarcoma patients with lung metastasis

To investigate the overall survival of post-resection leiomyosarcoma (LMS) patients with lung metastasis, data of post-resection LMS patients with lung metastasis between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical characteristics and survival data for post-resection LMS patients with lung metastasis at Tianjin Medical University Cancer Hospital & Institute (TJMUCH) between October 2010 and July 2018 were collected. Patients derived from the SEER database and TJMUCH were divided into training and validation cohorts, respectively. Univariate and multivariate Cox regression analyses were performed and a nomogram was established. The area under the curve (AUC) and the calibration curve were used to evaluate the nomogram. A web-based nomogram was developed based on the established nomogram. Eventually, 226 patients from the SEER database who were diagnosed with LMS and underwent primary lesion resection combined with lung metastasis were enrolled in the training cohort, and 17 patients from TJMUCH were enrolled in the validation cohort. Sex, race, grade, tumor size, chemotherapy, and bone metastasis were correlated with overall survival in patients with LMS. The C-index were 0.65 and 0.75 in the SEER and Chinese set, respectively. Furthermore, the applicable AUC values of the ROC curve in the SEER cohort to predict the 1-, 3-, 5- years survival rate were 0.646, 0.682, and 0.689, respectively. The corresponding AUC values in the Chinese cohort were 0.970, 0.913, and 0.881, respectively. The calibration curve showed that the nomogram performed well in predicting the overall survival in post-resection LMS patients with lung metastasis. A web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) was established. The web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) is an accurate and personalized tool for predicting the overall survival of post-resection LMS with lung metastasis.

Prediction of overall survival after radical gastrectomy using nomograms created by tumor markers

Prediction of prognosis after radical resection of gastric cancer has not been well established. Therefore, we aimed to establish a prognostic model based on a new score system of patients with gastric cancer. A total of 1235 patients who underwent curative gastrectomy at our hospital from October 2015 to April 2017 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. Construction of the nomogram was based on Cox proportional hazard regression models. The construction of the new score models was analyzed by the receiver operating characteristic curve (ROC curve), calibration curve, and decision curve. Multivariate analysis showed that tumor size, T, N, carcinoembryonic antigen, CA125, and CA19-9 were independent prognostic factors. The new score model had a greater AUC (The area under the ROC curve) than other systems, and the C-index of the nomogram was highly reliable for evaluating the survival of patients with gastric cancer. Based on the tumor markers and other clinical indicators, we developed a precise model to predict the prognosis of patients with gastric cancer after radical surgery. This score system can be helpful to both surgeons and patients.

Preclinical activity of selinexor in combination with eribulin in uterine leiomyosarcoma

Leiomyosarcoma (LMS) is a rare soft tissue sarcoma (STS) that begins in smooth muscle tissue and most often initiates in the abdomen or uterus. Compared with other uterine cancers, uterine LMS (ULMS) is an aggressive tumor with poor prognosis and a high risk of recurrence and death, regardless of the stage at presentation. Selinexor is a first-in-class selective inhibitor of nuclear export (SINE) compound that reversibly binds to exportin 1 (XPO1), thereby reactivating tumor suppressor proteins and downregulating the expression of oncogenes and DNA damage repair (DDR) proteins. In this study, we evaluated the effects of selinexor in combination with doxorubicin and eribulin in the LMS tumor model in vitro and in vivo. Treatment of selinexor combined with eribulin showed synergistic effects on tumor growth inhibition in SK-UT1 LMS-derived xenografts. Immunohistochemical assessment of the tumor tissues showed a significantly reduced expression of proliferation (Ki67) and XPO1 markers following combination therapy compared to the control group. Global transcriptome analyses on tumor tissue revealed that the combination therapy regulates genes from several key cancer-related pathways that are differentially expressed in ULMS tumors. To our knowledge, this is the first preclinical study demonstrating the anti-cancer therapeutic potential of using a combination of selinexor and eribulin in vivo. Results from this study further warrant clinical testing a combination of chemotherapy agents with selinexor to reduce the morbidity and mortality from ULMS.

Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study

OBJECTIVE

To explore the risk factors and develop a predictive model for postpartum hemorrhage in twin pregnancies.

METHODS

All patients who gave birth at Ningbo Women and Children's Hospital from January 2018 to August 2022 were recruited. Patients were randomly allocated to a training cohort (n[Formula: see text]1395) validation cohort (n[Formula: see text]650) at a 7:3 ratio. In the training cohort, LASSO regression for screening variables and multifactorial logistic regression analysis were performed to identify independent risk factors for postpartum hemorrhage in twin pregnancies. A nomogram was established based on the results of multiple logistic regression analysis. Nomogram performance was quantified using the receiver operating characteristic curve, Hosmer- Lemeshow test and decision curve analysis.

RESULTS

A total of 2045 patients were included in this study. Multifactorial Logistic regression analysis showed maternal age, assisted reproduction, platelet count, fibrinogen level, albumin level, hypertensive disorders of pregnancy, placenta praevia, number of previous cesarean deliveries, number of previous intrauterine manipulation, and neonatal weight were independent risk factors for postpartum hemorrhage in twin births. The area under curve (AUC) for the training cohort was 0.810 [95[Formula: see text] CI (0.781, 0.839)], with a sensitivity of 76.5[Formula: see text], specificity of 71.0[Formula: see text], and positive and negative predictive values of 0.358 and 0.935, respectively, while the AUC for the validation cohort was 0.821 [95[Formula: see text] CI (0.781, 0.860)], with a sensitivity of 80.9[Formula: see text], specificity of 69.49[Formula: see text], and positive predictive value and negative predictive value of 0.426 and 0.929, respectively.

CONCLUSION

The predictive model can effectively and quantitatively assess the risk of postpartum hemorrhage in twin pregnancies and help clinicians to take personalized preventive measures.

Nutritional and immune-related indicators-based Nomogram for predicting overall survival of surgical oral tongue squamous cell carcinoma

Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive oral tumors. The aim of this study was to establish a nomogram to predict overall survival (OS) of TSCC patients after surgery. 169 TSCC patients who underwent surgical treatments in the Cancer Hospital of Shantou University Medical College were included. A nomogram based on Cox regression analysis results was established and internally validated using bootstrap resampling method. pTNM stage, age and total protein, immunoglobulin G, factor B and red blood cell count were identified as independent prognostic factors to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of pTNM stage, indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected concordance index of nomogram was higher than that of pTNM stage (0.794 vs. 0.665, p = 0.0008). The nomogram also had a good calibration and improved overall net benefit. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (p < 0.0001). The nomogram based on nutritional and immune-related indicators represents a promising tool for outcome prediction of surgical OTSCC.

A personalized nomogram for predicting 3-year overall survival of patients with uterine carcinosarcoma in a tertiary care hospital in Southern Thailand

OBJECTIVE

To develop a nomogram for predicting 3-year overall survival (OS) and outcomes of surgically staged patients with uterine carcinosarcomas (UCS).

METHODS

This retrospective study analyzed the clinicopathological characteristics, treatment data, and oncological outcomes of 69 patients diagnosed with UCS between January 2002 and September 2018. Significant prognostic factors for OS were identified and integrated to develop a nomogram. Concordance probability (CP) was used as a precision measure. The model was internally validated using bootstrapping samples to correct overfitting.

RESULTS

The median follow-up time was 19.4 months (range, 0.77-106.13 months). The 3-year OS was 41.8% (95% confidence interval [CI], 29.9-58.3%). The International Federation of Gynecology and Obstetrics (FIGO) stage and adjuvant chemotherapy were independent factors for OS. The CP of the nomogram integrating with body mass index (BMI), FIGO stage, and adjuvant chemotherapy was 0.72 (95% CI, 0.70-0.75). In addition, the calibration curves for the probability of 3-year OS demonstrated good agreement between the nomogram-predicted and observed data.

CONCLUSION

The established nomogram using BMI, FIGO stage, and adjuvant chemotherapy accurately predicted the 3-year OS of patients with UCS. The nomogram was useful for patient counselling and deciding on follow-up strategies.

Development of a Nomogram to Predict the Outcome for Patients with Soft Tissue Sarcoma

Soft tissue sarcomas (STSs) are common cutaneous or subcutaneous neoplasms in dogs. Most STSs are initially treated by surgical excision, and local recurrence may develop in almost 20% of patients. Currently, it is difficult to predict which STS will recur after excision, but this ability would greatly assist patient management. In recent years, the nomogram has emerged as a tool to allow oncologists to predict an outcome from a combination of risk factors. The aim of this study was to develop a nomogram for canine STSs and determine if the nomogram could predict patient outcomes better than individual tumour characteristics. The current study provides the first evidence in veterinary oncology to support a role for the nomogram to assist with predicting the outcome for patients after surgery for STSs. The nomogram developed in this study accurately predicted tumour-free survival in 25 patients but failed to predict recurrence in 1 patient. Overall, the sensitivity, specificity, positive predictive, and negative predictive values for the nomogram were 96%, 45%, 45%, and 96%, respectively (area under the curve: AUC = 0.84). This study suggests a nomogram could play an important role in helping to identify patients who could benefit from revision surgery or adjuvant therapy for an STS.

Staging Systems and Nomograms for Soft Tissue Sarcoma

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new “dynamic” nomograms and prognostic tools have been developed, allowing doctors to “recalculate” a patient’s prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.

Ovarian, Uterine, and Vulvovaginal Cancers: Screening, Treatment Overview, and Prognosis

Ovarian, uterine, and vulvovaginal cancers affect approximately 96,000 women per year in the United States, resulting in approximately 29,000 deaths annually. Routine screening protocols do not detect these malignancies; thus, the recognition of risk factors and evaluation of worrisome symptoms are essential for early detection and improved prognoses. Treatment is managed by gynecologic oncologists, and often involves a combination of surgery, chemotherapy, and possible radiation treatments. Survivor care is managed by the primary-care clinician: expert attention to the mental, physical, and sexual health of each patient will ensure the best outcomes and quality of life.

Defining the relevance of surgical margins. Part two: Strategies to improve prediction of recurrence risk

Due to the complex nature of tumour biology and the integration between host tissues and molecular processes of the tumour cells, a continued reliance on the status of the microscopic cellular margin should not remain our only determinant of the success of a curative-intent surgery for patients with cancer. Based on current evidence, relying on a purely cellular focus to provide a binary indication of treatment success can provide an incomplete interpretation of potential outcome. A more holistic analysis of the cancer margin may be required. If we are to move ahead from our current situation - and allow treatment plans to be more intelligently tailored to meet the requirements of each individual tumour - we need to improve our utilisation of techniques that either improve recognition of residual tumour cells within the surgical field or enable a more comprehensive interrogation of tumour biology that identifies a risk of recurrence. In the second article in this series on defining the relevance of surgical margins, the authors discuss possible alternative strategies for margin assessment and evaluation in the canine and feline cancer patient. These strategies include considering adoption of the residual tumour classification scheme; intra-operative imaging systems including fluorescence-guided surgery, optical coherence tomography and Raman spectroscopy; molecular analysis and whole transcriptome analysis of tissues; and the development of a biologic index (nomogram). These techniques may allow evaluation of individual tumour biology and the status of the resection margin in ways that are different to our current techniques. Ultimately, these techniques seek to better define the risk of tumour recurrence following surgery and provide the surgeon and patient with more confidence in margin assessment.

Development and validation of a novel nomogram for predicting overall survival in gastric cancer based on inflammatory markers

BACKGROUND

Nearly 66% of occurrences of gastric cancer (GC), which has the second-highest death rate of all cancers, arise in developing countries. In several cancers, the predictive significance of inflammatory markers has been established.

AIM

To identify clinical characteristics and develop a specific nomogram to determine overall survival for GC patients.

METHODS

Nine hundred and four GC patients treated at the First Affiliated Hospital of Anhui Medical University between January 2010 and January 2013 were recruited. Prognostic risk variables were screened for Cox analysis. The C index, receiver operator characteristic (ROC) curve, and decision curve analysis were used to evaluate the nomogram.

RESULTS

Tumor node metastasis stage, carcinoembryonic antigen, systemic immune-inflammation index, and age were identified as independent predictive variables by multivariate analysis. Systemic immune-inflammation index value was superior to that of other inflammatory indicators. The ROC indicated the nomogram had a higher area under the curve than other factors, and its C-index for assessing the validation and training groups of GC patients was extremely reliable.

CONCLUSION

We created a novel nomogram to forecast the prognosis of GC patients following curative gastrectomy based on blood markers and other characteristics. Both surgeons and patients can benefit significantly from this new scoring system.

Clinical Analysis and Prognostic Prediction Model for Patients with Uterine Leiomyosarcoma at FIGO Stage I

Purpose

To reveal the clinical status and construct a predictive prognostic model for patients with uterine leiomyosarcoma (uLMS) at International Federation of Gynecology and Obstetrics (FIGO) stage I.

Patients and Methods

The medical records of patients with stage I uLMS during the study period were retrospectively reviewed. Multiple imputation, Martingale residuals and restricted cubic spline were used for data processing. Univariate and multivariate analyses were used to determine independent prognostic factors. The Schoenfeld individual test was used to verify the proportional hazards (PH) assumption. The predictive ability of the nomogram was validated internally.

Results

Ultimately, 102 patients were included. The median age at diagnosis was 51 years old. During the medium follow-up time of 68 months, 55 (53.9%) patients developed recurrence. The median recurrence interval was 32 months. The most common metastatic site was the lung (27 cases). Eventually, 38 (37.3%) patients died of uLMS. The 3-year and 5-year overall survival rates were 66.0% and 52.0%, respectively. Age at diagnosis >49 years, larger tumor size, MI>10/10HPF, presence of LVSI and Ki-67 labeling index (LI) >25% (P=0.0467, 0.0077, 0.0475, 0.0294, and 0.0427, respectively) were independent prognostic factors. The PH assumption remained inviolate. The concordance index was 0.847, the area under the time-dependent receiver operating characteristic curve surpassed 0.7, and the calibration curve showed gratifying consistency.

Conclusion

Age at diagnosis, tumor size, MI, LVSI, and Ki-67 LI were identified as independent prognostic factors for stage I uLMS. This prognostic nomogram would provide personalized assessment with superior predictive performance.

An Extremely Rare Case of Disseminated Peritoneal Leiomyomatosis with a Pelvic Leiomyosarcoma and Omental Metastasis after Laparoscopic Morcellation: Systematic Review of the Literature

Minimally invasive treatment of uterine fibroids usually requires a power morcellation, which could be associated with several complications. A rare sequela is disseminated peritoneal leiomyomatosis. Indeed, recurrence or metastasis in these cases could be attributed to iatrogenic or under-evaluation of primary tumors, although a subset of cases is a sporadic sample of biological progression. We present an extremely rare case of a patient who underwent laparoscopic morcellation and after 12 years developed a pelvic leiomyosarcoma with two omental metastases, disseminated peritoneal leiomyomatosis with a parasite leiomyoma with bizarre nuclei and a parasite cellular leiomyoma simultaneously. The diagnosis was predicted preoperatively by an expert sonographer who recognized the ultrasound characteristics of uterine sarcoma and the localization of some of the masses, so the patient was referred to the gynaecological oncologists who could appropriately treat her. We present here a case report and a systematic review that could be a useful tool for further discussion and future clinical practice guidelines.

The Potential Prognostic and Therapeutic Implications of Prolactin Receptor and Growth Hormone-releasing Hormone Receptor Expression in Uterine Leiomyosarcomas

The management of uterine leiomyosarcomas (uLMS) remains challenging. The rate of recurrence and metastasis is high, with 5-yr survival reaching only 40% to 50% in patients with tumor confined to the uterus (FIGO stage I or II). Prolactin receptor (PRLR) and growth hormone-releasing hormone receptor (GHRHR) have been implicated in the carcinogenesis of malignant tumors of the breast, endometrium, ovary, liver, and prostate. GHRHR antagonists inhibit in vitro growth of many human tumors and the expression of PRLR is associated with resistance to chemotherapy. The immunohistochemical expression of PRLR and GHRH in 24 primary and 2 recurrent uLMS was evaluated. Representative sections were stained with PRLR and GHRHR antibodies and immunoreactivity was calculated using H -score. The results were correlated with clinicopathologic data using Kaplan-Meier survival and multivariable Cox proportion hazard regression analyses. All tumors were positive for both markers with predominantly moderate to strong expression of PRLR (89%) and GHRHR (82%). Patients with tumors showing moderate to strong expression of PRLR were significantly less likely to achieve disease-free survival ( P =0.004) and significantly more likely to have a poor overall survival ( P =0.049). No significant difference in mean PRLR expression was found between tumors with higher mitotic counts (>20/10 hpf) and lower mitotic counts (20 or less/10 hpf). Furthermore, in 2 patients where the primary and recurrent tumors were tested, there was stronger expression of PRLR in the recurrence compared with the primary. This correlation was not found with GHRHR. Both PRLR and GHRHR may play a role in carcinogenesis in uLMS, as they do in other malignant neoplasms. To our knowledge, this study is the first evaluating the expression of these receptors in uLMS. Moderate or high expression of PRLR may serve as a prognostic marker associated with recurrences and increased mortality in uLMS patients.

Effect of tumor morcellation in patients with early uterine sarcoma: a multicenter study in Germany

Objective

The use of power morcellation at laparoscopy may worsen survival rates for patients with malignancy. The aim of the present study was to report the outcome of patients with early-stage uterine sarcoma after morcellation or total en-bloc resection, and evaluate potential signs of sarcoma preoperatively.

Material and Methods

This multicenter retrospective study consisted of patients, who underwent surgery for FIGO-stage-1 uterine sarcoma. Twenty-four patients were divided into a non-morcellation group and a morcellation group. Clinical records and the outcomes of patients, including one-, three- and five-year survival rates were reviewed. Preoperative characteristics of patients with sarcoma were compared to those of a control group with uterine myoma (1:4 ratio), matched by age and type of operation.

Results

Obesity was an independent risk factor for uterine myoma. Tumor growth, solitary growth, largest-diameter lesion >8.0 cm, and anechoic areas suggesting necrosis and increased vascularization were significantly more common in the sarcoma group. A large tumor diameter was significantly associated with mortality. Patients in the non-morcellation group had a slightly lower disease-free survival, but poorer overall survival (OS) rates compared to patients in the morcellation group, but neither difference was statistically significant. Patients in the non-morcellation group, who had undergone a re-exploration experienced late recurrence, but no upstaging was evident after the operation.

Conclusion

Preoperative ultrasound characteristics could be useful to distinguish sarcoma from leiomyoma of uterus. Morcellation of a sarcoma may increase abdominal and pelvic recurrence rates, but may not be associated with OS in patients with FIGO-stage-1 disease.

A novel morphology-based risk stratification model for stage I uterine leiomyosarcoma: an analysis of 203 cases

Uterine leiomyosarcoma is the most common uterine mesenchymal malignancy. The majority present at stage I, and clinical outcomes vary widely. However, no widely accepted risk stratification system for stage I uterine leiomyosarcoma is currently available. We studied 17 routinely evaluated clinicopathologic parameters in 203 stage I uterine leiomyosarcoma from three institutions to generate a novel risk stratification model for these tumors. Mitoses >25 per 2.4 mm2 (10 high-power fields), atypical mitoses, coagulative necrosis, lymphovascular invasion, and serosal abutment were significantly associated with disease-free and disease-specific survival in univariate and multivariate analyses. These prognostic parameters were each scored as binary ("yes" or "no") variables and fitted to a single optimized algebraic risk model:Risk score = (coagulative necrosis)(1) + (mitoses > 25 per 2.4 mm2)(2) + (atypical mitoses)(2) + (lymphovascular invasion)(3) + (serosal abutment)(5)By logistic regression, the risk model was significantly associated with 5-year disease-free (AUC = 0.9270) and 5-year disease-specific survival (AUC = 0.8517). Internal and external validation substantiated the model. The continuous score (range, 0-13) was optimally divided into 3 risk groups with distinct 5-year disease-free and disease-specific survival: low risk (0-2 points), intermediate risk (3-5 points), and high risk (6-13 points) groups. Our novel risk model performed significantly better than alternative uterine leiomyosarcoma risk stratification systems in predicting 5-year disease-free and disease-specific survival in stage I tumors. A simplified risk model, omitting terms for serosal abutment and lymphovascular invasion, can be accurately applied to myomectomy or morcellated specimens. We advocate routine application of this novel risk model in stage I uterine leiomyosarcoma to facilitate patient counseling and proper risk stratification for clinical trials.

Executive Summary of the Uterine Cancer Evidence Review Conference

Evidence for uterine cancer prevention, diagnosis, and special issues from the Uterine Cancer Evidence Review Conference is summarized.

The Centers for Disease Control and Prevention recognized the need for educational materials for clinicians on the prevention and early diagnosis of gynecologic cancers. The American College of Obstetricians and Gynecologists convened a panel of experts in evidence review from the Society for Academic Specialists in General Obstetrics and Gynecology and content experts from the Society of Gynecologic Oncology to review relevant literature, best practices, and existing practice guidelines as a first step toward developing evidence-based educational materials for women's health care clinicians about uterine cancer. Panel members conducted structured literature reviews, which were then reviewed by other panel members and discussed at a virtual meeting of stakeholder professional and patient advocacy organizations in January 2021. This article is the evidence summary of the relevant literature and existing recommendations to guide clinicians in the prevention, early diagnosis, and special considerations of uterine cancer. Substantive knowledge gaps are noted and summarized to provide guidance for future research.

Impact of Surgery and Chemotherapy on Metastatic Extrauterine Leiomyosarcoma

Background: Few studies have described the characteristics and prognostic factors of patients with metastatic extrauterine leiomyosarcoma (euLMS). Therefore, we retrospectively investigated the clinicopathological features, clinical outcomes, and prognostic factors of patients with euLMS. Methods: We recruited 61 patients with metastatic euLMS treated from 2006 to 2020 and collected and statistically analyzed information on patient-, tumor-, and treatment-related factors. The median follow-up period was 21.1 months. Results: Sixty-one patients with euLMS and a median age of 59 years were included. Furthermore, their five-year overall survival (OS) rate was 38.3%. Univariate analysis revealed that primary tumor size >10 cm, synchronous metastasis, initial metastatic sites >1, and no metastasectomy with curative intent were significantly associated with poor OS rate. Multivariate analysis identified primary tumor size >10 cm as an independent prognostic factor for poor OS. Among 24 patients who received metastasectomy with curative intent, the interval from the initial diagnosis to development of metastasis ≤6 months was significantly correlated with unfavorable OS. Among 37 patients who did not receive metastasectomy, chemotherapy after metastasis development was significantly related to better OS. Conclusions: Complete metastasectomy should be considered for metastatic euLMS treatment. Moreover, chemotherapy could prolong survival in patients with metastasis who are ineligible for metastasectomy.

Retrospective analysis of adjuvant treatment for localized, operable uterine leiomyosarcoma

OBJECTIVE

Currently, there is no standard adjuvant treatment protocol for localized uterine leiomyosarcoma (uLMS) as clinical trials to address this question have been retrospective, underpowered, or undermined by slow accrual rates. The aim of this study is to determine the benefit of adjuvant chemotherapy for uLMS.

METHODS

We reviewed the medical records of localized uLMS patients who had underwent adjuvant therapy after upfront surgery between 2000 and 2020. The cases were blinded for review. We evaluated the influence of various clinical characteristics and different types of adjuvant therapies on specific outcomes.

RESULTS

Sixty-eight patients (median age: 50 years) were included for analysis. Forty of 68 (58.8%) patients received adjuvant chemotherapy +/- radiation therapy and 25 patients (38.6%) did not receive any adjuvant therapy. At a median follow-up time of 43.3 months, 45 patients (66.1%) had relapsed disease. The median disease-free survival (mDFS) for all patients was 23.1 months. Patients who received any adjuvant treatment (chemotherapy and/or radiation) trended toward a longer mDFS compared with those who did not receive any adjuvant therapy (29.7 vs. 14.1 months, p = 0.26). Patients who received adjuvant chemotherapy alone had a longer, but nonstatistically significant mDFS compared with those who did not receive any adjuvant treatment (22.2 vs. 14.1 months, p = 0.18). Additionally, univariate analysis found that tumor size large than 10 cm, and a mitotic rate >10/10hpf were independent prognostic factors for worse DFS.

CONCLUSIONS

Though DFS was more favorable among those who received adjuvant therapy, it was not statistically significant, and thus based on this data adjuvant therapy for resected uLMS is still in question.

A case of metastatic endobronchial tumor from uterine leiomyosarcoma

A 54-year-old woman presented with persistent productive cough, found to have an endobronchial tumor which obstructed the left upper lobe bronchus. Histopathological examination of a transbronchial biopsy of the endobronchial tumor suggested leiomyosarcoma. A positron emission tomography (PET)-CT revealed uterus tumor with moderate uptake of ¹⁸F-fluorodeoxyglucose, suggesting uterine malignancies. From the results of histological findings of the resected uterus and the biopsied bronchial specimen, she was diagnosed with uterine leiomyosarcoma and endobronchial metastasis. The systematic use of PET-CT could be useful for patients presenting with tumors that cause endobronchial metastasis of leiomyosarcomas.

Nomogram based on clinical characteristics and serological inflammation markers to predict overall survival of oral tongue squamous cell carcinoma patient after surgery

BACKGROUND

Oral tongue squamous cell carcinoma (OTSCC) is a prevalent malignant disease that is characterized by high rates of metastasis and postoperative recurrence. The aim of this study was to establish a nomogram to predict the outcome of OTSCC patients after surgery.

METHODS

We retrospectively analyzed 169 OTSCC patients who underwent treatments in the Cancer Hospital of Shantou University Medical College from 2008 to 2019. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient's overall survival (OS). A nomogram based on these prognostic factors was established and internally validated using a bootstrap resampling method.

RESULTS

Multivariate Cox regression analysis revealed the independent prognostic factors for OS were TNM stage, age, lymphocyte-to-monocyte ratio and immunoglobulin G, all of which were identified to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of TNM stage (292.222 vs. 305.480; 298.444 vs. 307.036, respectively), indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected of concordance index (C-index) of nomogram was 0.784 (95% CI 0.708-0.860), which was higher than that of TNM stage (0.685, 95% CI 0.603-0.767, P = 0.017). The results of time-dependent C-index for OS also showed that the nomogram had a better discriminative ability than that of TNM stage. The calibration curves of the nomogram showed good consistency between the probabilities and observed values. The decision curve analysis also revealed the potential clinical usefulness of the nomogram. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (P < 0.0001).

CONCLUSIONS

The nomogram based on clinical characteristics and serological inflammation markers might be useful for outcome prediction of OTSCC patient.

Risk factors for the development of local recurrence in extremity soft-tissue sarcoma

INTRODUCTION

Local recurrence (LR) is one of the main pitfalls in surgery for extremities soft tissue sarcoma (eSTS). Achieving clear histopathological margins is the most important factor to reduce the risk of LR, but the ability to do so depends on not only surgical technique but also the interplay between tumor biology, anatomical location and surgical approach. The balance between postoperative morbidity and oncological benefits in reducing the risk of LR needs to be considered.

AREAS COVERED

This review will cover which etiological factors for the development of eSTS lead to an increased risk of LR and discuss histological subtypes that have a high risk of LR and which surgical and neoadjuvant therapeutic strategies can minimize the risk of LR.

EXPERT OPINION

The traditional view that surgical radicality always results in low rates of LR, while marginality alone always leads to high rates of relapse, is outdated. In the modern era of surgical oncology, limb salvage and high-level function after resectional surgery are the key surgical goals. The best results are achieved by combining effective neoadjuvant treatments with planned bespoke oncological operations that consider the biological and anatomical factors of each individual sarcoma.

Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Serous ovarian cancer is the most common and primary death type in ovarian cancer. In recent studies, tumor microenvironment and tumor immune infiltration significantly affect the prognosis of ovarian cancer. This study analyzed the four gene expression types of ovarian cancer in TCGA database to extract differentially expressed genes and verify the prognostic significance. Meanwhile, functional enrichment and protein interaction network analysis exposed that these genes were related to immune response and immune infiltration. Subsequently, we proved these prognostic genes in an independent data set from the GEO database. Finally, multivariate cox regression analysis revealed the prognostic significance of TAP1 and CXCL13. The genetic alteration and interaction network of these two genes were shown. Then, we established a nomogram model related to the two genes and clinical risk factors. This model performed well in Calibration plot and Decision Curve Analysis. In conclusion, we have obtained a list of genes related to the immune microenvironment with a better prognosis for serous ovarian cancer, and based on this, we have tried to establish a clinical prognosis model.

Second Primary Malignancies in Patients With Hepatocellular Carcinoma: A Population-Based Analysis

Background

Second primary malignancy (SPM) is becoming a threat for the health of cancer survivors. However, data on the features and results of patients with hepatocellular carcinoma (HCC) with SPMs are scarce. This study aimed to explore the characteristics of HCC patients with SPMs and to screen HCC patients who are at a high risk of developing SPMs.

Method

HCC patients diagnosed between 2000 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. Eligible patients were divided into the only one primary malignancy and SPM groups. The Fine-Gray proportional subdistribution hazards model was used to explore the risk factors of developing SPMs, and a competing-risk model was established to predict the probability of developing SPMs for HCC patients after initial diagnosis. The calibration curves, concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram.

Results

A total of 40,314 HCC patients were identified, 1,593 (3.95%) of whom developed SPMs 2 months after the initial diagnosis with a maximum follow-up time of approximately 18 years. The 3-, 5-, and 10-year cumulative incidence of SPMs were 2.35%, 3.12%, and 4.51%, respectively. Age at initial diagnosis, extent of disease, tumor size, and treatment were identified as the independent risk factors of developing SPMs and integrated into the competing-risk nomogram. The C-index of the nomogram was 0.677 (95% confidence interval 0.676-0.678), and the calibration curves showed an excellent agreement between the nomogram prediction and the actual observations. Furthermore, DCA indicated that the nomogram had good net benefits in clinical scenarios.

Conclusions

HCC survivors remain at a high risk of developing SPMs. The development of SPMs was associated with the clinical features and treatment strategies. A competing-risk nomogram was constructed to help surgeons identify the patients who are at a high risk of developing SPMs and contribute to the further management of SPMs.

Development of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study)

Simple Summary

Uterine leiomyosarcoma is an aggressive tumor and the current staging system cannot differentiate the patients into different prognostic groups. This leads to difficulty in predicting the patients’ outcomes and planning for adjuvant therapy. We aimed to develop a prediction model that can predict the chance of survival by the third year. In this article, we had used different statistical tests to identify five readily available clinicopathologic parameters to build the prediction model. Internal validation was performed with satisfactory accuracy. Such a prediction model might help to predict survival outcome, and guide future research on the treatment modality.

Abstract

Background: The existing staging systems of uterine leiomyosarcoma (uLMS) cannot classify the patients into four non-overlapping prognostic groups. This study aimed to develop a prediction model to predict the three-year survival status of uLMS. Methods: In total, 201 patients with uLMS who had been treated between June 1993 and January 2014, were analyzed. Potential prognostic indicators were identified by univariate models followed by multivariate analyses. Prediction models were constructed by binomial regression with 3-year survival status as a binary outcome, and the final model was validated by internal cross-validation. Results: Nine potential parameters, including age, log tumor diameter, log mitotic count, cervical involvement, parametrial involvement, lymph node metastasis, distant metastasis, tumor circumscription and lymphovascular space invasion were identified. 110 patients had complete data to build the prediction models. Age, log tumor diameter, log mitotic count, distant metastasis, and circumscription were significantly correlated with the 3-year survival status. The final model with the lowest Akaike’s Information Criterion (117.56) was chosen and the cross validation estimated prediction accuracy was 0.745. Conclusion: We developed a prediction model for uLMS based on five readily available clinicopathologic parameters. This might provide a personalized prediction of the 3-year survival status and guide the use of adjuvant therapy, a cancer surveillance program, and future studies.

Model to Predict Overall Survival in Patients With Hepatocellular Carcinoma After Curative Hepatectomy

Background

The prognosis of patients with hepatocellular carcinoma (HCC) remains difficult to accurately predict. The purpose of this study was to establish a prognostic model for HCC based on a novel scoring system.

Methods

Five hundred and sixty patients who underwent a curative hepatectomy for treatment of HCC at our hospital between January 2007 and January 2014 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. The nomogram construction was based on Cox proportional hazard regression models, and the development of the new scoring model was analyzed using receiver operating characteristic (ROC) curve analysis and then compared with other clinical indexes. The novel scoring system was then validated with an external dataset from a different medical institution.

Results

Multivariate analysis showed that tumor size, portal vein tumor thrombus (PVTT), invasion of adjacent tissues, microvascular invasion, and levels of fibrinogen and total bilirubin were independent prognostic factors. The new scoring model had higher area under the curve (AUC) values compared to other systems, and the C-index of the nomogram was highly consistent for evaluating the survival of HCC patients in the validation and training datasets, as well as the external validation dataset.

Conclusions

Based on serum markers and other clinical indicators, a precise model to predict the prognosis of patients with HCC was developed. This novel scoring system can be an effective tool for both surgeons and patients.

Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas

Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of 'high-risk' patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients.

[Interdisciplinary S2k guidelines on the diagnosis and treatment of uterine sarcomas-recommendations for surgical pathology]

Uterine sarcomas represent a heterogeneous group of rare malignancies, derived from the myometrium, the endometrial stroma, and very rarely from the nonspecialized uterine soft tissue. The actual incidence is about 1.5 for Caucasian and 3.0 for Afro-American women. There is no grading system for leimoysarcoma defined by the WHO classification; however, if clinicians request, the FNCLCC grading can be specified in analogy to soft tissue sarcomas. Adenosarcomas must be distinguished from adenofibromas (the existence of which is questionable)-with the vast majority of these tumors being uterine adenosarcomas. Within adenosarcomas, deep myometrial invasion (>50%), sarcomatous overgrowth, and a high-grade heterologous component are associated with a higher recurrence rate and poor survival. The immunohistochemical panel represents a very helpful tool for distinguishing low-grade from high grade endometrial stromal sarcomas (ESS) and may be supplemented by molecular analyses. Steroid hormone receptor analysis should be performed for all ESS due to the possible therapeutic relevance. Undifferentiated uterine sarcomas represent a diagnosis of exclusion and have a very poor prognosis. Carcinosarcomas represent a special subtype of endometrial carcinomas and are in fact not uterine sarcomas. Uterine sarcomas may present substantial intratumoral heterogeneity and adequate embedding is mandatory. Lesions ≤2 cm in the largest dimension should be processed completely and larger tumors should be processed with one block per centimeter for the largest tumor dimension.

The impact of tumor fragmentation in patients with stage I uterine leiomyosarcoma on patterns of recurrence and oncologic outcome

OBJECTIVE

To evaluate the impact of tumor fragmentation on oncologic outcomes in patients with stage I uterine leiomyosarcoma (uLMS).

METHODS

We identified all patients diagnosed with stage I uLMS presenting to our institution within three months of primary surgery, 1/2000-1/2019. Patients with recurrent disease were excluded. The non-morcellated group had total hysterectomy without documented specimen fragmentation; the morcellated group, total hysterectomy with documented specimen fragmentation. We defined fragmentation as manual fragmentation or morcellation (via power morcellator or otherwise) of the specimen in peritoneal cavity or vagina. Appropriate statistical analyses were performed.

RESULTS

152 patients met inclusion criteria. 107 (70%) underwent total hysterectomy (non-morcellated); 45 (30%) underwent morcellation. Median age at diagnosis for the entire cohort was 55 years (range 30-91). Median follow-up was 42.1 months (range 1.1-197.8). 40 (26.3%) patients had primary surgery at our institution, 112 (73.7%) at an outside hospital. In total 110 (72.3%) recurred: 72/107 (67.2%) non-morcellated; 38/44 (86.3%) morcellated. Median progression-free survival (PFS) for non-morcellated versus morcellated was 13.8 (95%CI 9.2-20.2) versus 7.3 months (95%CI 3-13.1), HR 1.5 (95%CI 1.02-2.24); P = 0.04. Median overall survival (OS) for non-morcellated versus morcellated was 82.1 (95%CI 52.4-122) versus 47.8 months (95%CI 28.5-129.6), HR 1.1 (95%CI 0.67-1.82); P = 0.7. Among patients with recurrence, 69.4% of non-morcellated recurred at hematogenous sites only, 18.1% recurred in peritoneum only; 28.9% of morcellated recurred at hematogenous sites, 63.2% in peritoneum. Race, lymphovascular invasion, postoperative chemotherapy, were independently associated with PFS. Mitotic index was independently associated with OS.

CONCLUSIONS

Tumor fragmentation/morcellation was associated with significantly higher risk of recurrence and a nearly 4-fold increase in peritoneal recurrence. Prognostic biomarkers remain important in predicting oncologic outcomes, independent of fragmentation or treatment.

Digital Quantification of Ki-67 and PHH3 in the Classification of Uterine Smooth Muscle Tumors

Uterine smooth muscle tumors are the most common tumors of the female genital tract and include leiomyoma (LM) and its variants, smooth muscle tumors of uncertain malignant potential (STUMP), and leiomyosarcoma (LMS). Accurate diagnosis of LMS is determined by nuclear atypia, mitotic count, and the presence or absence of tumor cell necrosis, a process which is often difficult and subjective. In this study, we correlated digital quantification of proliferation marker Ki-67 and mitotic marker phosphohistone H3 (PHH3) to mitotic count, classification of uterine smooth muscle tumors, and clinical outcomes. A total of 39 cases (17 LMS, 5 STUMP, 10 LM with bizarre nuclei, and 7 LM) were included. Mitotic count, Ki-67, and PHH3 were significantly correlated. When comparing the LMS group to the STUMP, LM with bizarre nuclei, and LM groups combined, LMS showed a significantly greater digital quantification of Ki-67 (median 10.6% vs. 0.4%, P<0.001) and PHH3 (median 0.5% vs. 0.14%, P=0.022). Ki-67 was a better predictor of LMS compared with PHH3 (area under the curve 0.92 vs. 0.73, P=0.017). Above a threshold Ki-67 value of 3.8%, the sensitivity was 82% and specificity was 91%. Clinical outcomes were available for 10 patients (8 LMS and 2 STUMP), and inferior progression-free survival was noted for patients with higher Ki-67 values. Overall, this study suggests that digital quantification of Ki-67 can potentially aid in diagnosis of LMS.

Molecular prognostication of uterine smooth muscle neoplasms: From CGH array to CINSARC signature and beyond

Uterine leiomyoma and leiomyosarcoma are located at the ends of the spectrum of smooth muscle lesions. Leiomyosarcoma belongs to the complex genomic sarcomas characterized by complex karyotypes. In contrast, leiomyoma, has a low level of chromosomal complexity. The analysis of genomic profiles of uterine smooth muscle tumors shows that genomic complexity, which is an expression of chromosomal instability, correlates with the metastatic potential and malignity of tumors: the more genetically complex a smooth muscle tumor is, the more malignant is its progression. In uterine tumors with uncertain malignant potential, the assessment of genomic index by CGH array, that is, counting the genomic complexity of a tumor, allows tumors with a risk of recurrence such as leiomyosarcomas to be distinguished from benign tumors like leiomyomas. The prognosis of leiomyosarcoma is poor and the most powerful prognostic factor so far is stage, as the histologic grade is not informative. In the quest to find efficient molecular prognostic factors, the transcriptomic signature CINSARC Nanocind, a mirror of chromosomic complexity and instability, outperforms stage, in both overall and recurrence-free survival. Genomic index and the CINSARC signature will contribute to improving diagnoses, therapeutic strategies, and randomization in future clinical trials. The biological understanding of the links between the CINSARC signature and metastatic mechanisms may lead to the development of new drugs. Furthermore, ctDNA is a promising new technique to detect residual disease and early recurrence.

A nomogram based on glycomic biomarkers in serum and clinicopathological characteristics for evaluating the risk of peritoneal metastasis in gastric cancer

Background

Peritoneal metastasis (PM) in gastric cancer (GC) remains an untreatable disease, and is difficult to diagnose preoperatively. Here, we aim to establish a novel prediction model.

Methods

The clinicopathologic characteristics of a cohort that included 86 non-metastatic GC patients and 43 PMGC patients from Zhongshan Hospital were retrospectively analysed to identify PM associated variables. Additionally, mass spectrometry and glycomic analysis were applied in the same cohort to find glycomic biomarkers in serum for the diagnosis of PM. A nomogram was established based on the associations between potential risk variables and PM.

Results

Overexpression of 4 N-glycans (H6N5L1E1: m/z 2620.93; H5N5F1E2: m/z 2650.98; H6N5E2, m/z 2666.96; H6N5L1E2, m/z 2940.08); weight loss ≥ 5 kg; tumour size ≥ 3 cm; signet ring cell or mucinous adenocarcinoma histology type; poor differentiation; diffuse or mixed Lauren classification; increased CA19-9, CA125, and CA724 levels; decreased lymphocyte count, haemoglobin, albumin, and pre-albumin levels were identified to be associated with PM. A nomogram that integrated with five independent risk factors (weight loss ≥ 5 kg, CA19-9 ≥ 37 U/mL, CA125 ≥ 35 U/mL, lymphocyte count < 2.0 * 10 ~ 9/L, and H5N5F1E2 expression ≥ 0.0017) achieved a good performance for diagnosis (AUC: 0.892, 95% CI 0.829–0.954). When 160 was set as the cut-off threshold value, the proposed nomogram represented a perfectly discriminating power for both sensitivity (0.97) and specificity (0.88).

Conclusions

The nomogram achieved an individualized assessment of the risk of PM in GC patients; thus, the nomogram could be used to assist clinical decision-making before surgery.

Risk factors and a predictive nomogram for lymph node metastasis of superficial esophagogastric junction cancer

BACKGROUND AND AIM

No predictive model for lymph node metastasis (LNM) of superficial esophagogastric junction (EGJ) cancer exists. This study aimed to evaluate incidence, identify risk factors, and develop a predictive nomogram for LNM in patients with superficial EGJ cancers.

METHODS

Data were extracted from the Surveillance, Epidemiology, and End Results database for model development and internal validation. Another data set was obtained from two hospitals for external validation. A nomogram was developed based on independent risk factors that resulted from a multivariate logistic regression analysis. Internal and external validations were performed to assess the performance of nomogram model by receiver operating characteristic and calibration plot.

RESULTS

Prevalence of LNM was 11.41% for intramucosal cancer and increased to 26.50% for submucosal cancer. On the multivariate analysis, large tumor size (odds ratio [OR] = 1.42; P < 0.001), moderately and poorly/un-differentiated pathological type (OR = 5.62 and 7.67; P = 0.024 and 0.008, respectively), and submucosal invasion (OR = 2.73; P = 0.004) were independent risk factors of LNM. The nomogram incorporating these three predictors demonstrated good discrimination (area under the estimated receiver operating characteristic curve [AUC]: 0.74; 95% confidence interval [95%CI]: 0.68, 0.80) and calibration (mean absolute error was 0.012). Moreover, the discrimination in the internal and external validation sets was good (AUC: 0.73 [95%CI: 0.66, 0.81] and 0.74 [95%CI: 0.60, 0.89], respectively). Nomogram provided better clinical usefulness as assessed by a decision curve analysis.

CONCLUSIONS

Prevalence of LNM in superficial EGJ cancer was high. The first risk-predictive nomogram model for LNM of superficial EGJ cancer may help clinicians to decide optimal treatment option preoperatively.

Outcomes of patients with pelvic leiomyosarcoma treated by surgery and relevant auxiliary diagnosis

BACKGROUND

Leiomyosarcoma is a subtype of soft tissue sarcoma with adverse outcomes. Leiomyosarcoma accounts for nearly 70% of all uterine sarcomas and is responsible for a considerable proportion of deaths because of uterine cancer. Clinical characteristics and relevant diagnosis of pelvic leiomyosarcoma should be further explored.

AIM

To identify the outcome and relevant perioperative evaluation of patients with pelvic leiomyosarcoma.

METHODS

The Kaplan-Meier method was used to determine progression-free survival and overall survival rates. Factors predictive of outcomes were identified using univariate and multivariate Cox proportional hazards models.

RESULTS

Fifty-one patients with pelvic leiomyosarcoma were enrolled and divided into two groups including uterine leiomyosarcoma and non-uterine leiomyosarcoma. Overall, 28.6% and 45.5% of uterine leiomyosarcoma and non-uterine leiomyosarcoma patients, respectively, had elevated carbohydrate antigen 125 levels, whereas 45.7% and 68.8%, respectively, underwent ultrasonography. Although 68.8% of uterine leiomyosarcoma patients were initially diagnosed with hysteromyoma, 72.7% of non-uterine leiomyosarcoma patients had pelvic and abdominal masses. Moreover, 93.3% of the recurrent lesions were detected using ultrasonography. Patients with International Federation of Gynaecology and Obstetrics (FIGO) stages III–IV disease had poorer progression-free survival values than those with FIGO stages I–II (P = 0.027) disease. FIGO stage was significantly associated with poor progression-free survival in the univariate (hazard ratio = 2.64, P = 0.03) and multivariate (hazard ratio = 2.49, P = 0.048) analyses.

CONCLUSION

Serum tumour biomarkers cannot be used for pelvic leiomyosarcoma diagnosis. FIGO stage is critical to predict the outcome of uterine leiomyosarcoma. Ultrasonography is more reliable for postoperative follow-up than preoperative diagnosis.

A Simple Model Established by Blood Markers Predicting Overall Survival After Radical Resection of Pancreatic Ductal Adenocarcinoma

Background: The prognostic prediction after radical resection of pancreatic ductal adenocarcinoma (PDAC) has not been well-established. We aimed to establish a prognostic model for PDAC based on a new score system, which included a clinical routine serum marker.

Methods: A total of 438 patients who underwent curative PDAC at the First Affiliated Hospital of Anhui Medical University from January 2007 to January 2014 were included in this study. Univariate and multivariate analyses were used to screen for prognostic risk factors. We constructed the nomogram based on Cox proportional hazard regression models. The construction of the new score models was analyzed by the receiver operator characteristic curve (ROC curve), which were compared with other clinical indexes.

Results: Multivariate analysis showed that TNM stage, CA199, CEA, globulin, neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) were independent prognostic factors. The new score system had a higher AUC value than other risk factors, and the C-index of the nomogram was highly consistent for evaluating survival of PDAC patients in the validation groups and training group, and the external population also verified the nomogram.

Conclusions: For the patients with PDAC after radical surgery, we developed a precise model to predict the prognosis based on the serum markers and other clinical indicators. For surgeons and patients, this score system can be an effective help.

Primary leiomyosarcoma of the uterine cervix: report of 4 cases, systematic review, and meta-analysis

BACKGROUND

Primary cervical leiomyosarcomas (CLMS) constitute 21% of all cervical sarcomas. Because of their rarity, to our knowledge, fewer than 40 cases have been reported. The aim of this study is to evaluate the clinical and surgical-pathological features, prognosis, treatment options, and survival of primary CLMS.

METHODS

A systematic review of the medical literature was conducted to evaluate articles about primary CLMS. The literature was searched between 1959 and May 2019. On final evaluation, there were 29 articles (one consisted of 8 cases; one consisted of 3 cases) and 42 cases with the addition of our 4 cases.

RESULTS

Age (⩾48 versus ⩽47 years) (hazard ratio.HR], 4.528; 95% confidence interval.CI], 1.550-13.227; p=0.006) and mitoses count (<10/10 high-power field [HPF] versus ⩾10/10 HPF) (HR, 3.865; 95% CI, 1.046-14.278; p=0.043) are independent prognostic factors for recurrence and age (HR, 5.318; 95% CI, 1.671-16.920; p=0.005) and hysterectomy (performed versus not performed) (HR, 4.377; 95% CI, 1.341-14.283; p=0.014) are independent prognostic factors for death because of disease on multivariate analysis.

CONCLUSIONS

Information on primary CLMS is sparse and obtained from rare case reports and case series. Hysterectomy must be the first choice of treatment in these patients according to our results on multivariate analysis. The type of hysterectomy does not have an effect on oncologic outcome. Radical hysterectomy is not obligatory and more data are needed to make more accurate conclusions.