What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

Background: Tumor size assessment by MRI is central for staging uterine cervical cancer. However, the optimal role of MRI-derived tumor measurements for prognostication is still unclear. Material and methods: This retrospective cohort study included 416 women (median age: 43 years) diagnosed with cervical cancer during 2002–2017 who underwent pretreatment pelvic MRI. The MRIs were independently read by three radiologists, measuring maximum tumor diameters in three orthogonal planes and maximum diameter irrespective of plane (MAXimaging). Inter-reader agreement for tumor size measurements was assessed by intraclass correlation coefficients (ICCs). Size was analyzed in relation to age, International Federation of Gynecology and Obstetrics (FIGO) (2018) stage, histopathological markers, and disease-specific survival using Kaplan–Meier-, Cox regression-, and time-dependent receiver operating characteristics (tdROC) analyses. Results: All MRI tumor size variables (cm) yielded high areas under the tdROC curves (AUCs) for predicting survival (AUC 0.81–0.84) at 5 years after diagnosis and predicted outcome (hazard ratios [HRs] of 1.42–1.76, p < 0.001 for all). Only MAXimaging independently predicted survival (HR = 1.51, p = 0.03) in the model including all size variables. The optimal cutoff for maximum tumor diameter (≥ 4.0 cm) yielded sensitivity (specificity) of 83% (73%) for predicting disease-specific death after 5 years. Inter-reader agreement for MRI-based primary tumor size measurements was excellent, with ICCs of 0.83–0.85. Conclusion: Among all MRI-derived tumor size measurements, MAXimaging was the only independent predictor of survival. MAXimaging ≥ 4.0 cm represents the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. Inter-reader agreement for MRI-based tumor size measurements was excellent.publishedVersio

Interobserver agreement and prognostic impact for MRI–based 2018 FIGO staging parameters in uterine cervical cancer

Objectives To evaluate the interobserver agreement for MRI–based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers. Methods This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI–derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan–Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics. Results Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI–derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI–based staging parameters improved risk stratification when compared to corresponding clinical assessments alone. Conclusion The interobserver agreement for central MRI–derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer.publishedVersio

Preoperative pelvic MRI and 2-[18F]FDG PET/CT for lymph node staging and prognostication in endometrial cancer—time to revisit current imaging guidelines?

Objective This study presents the diagnostic performance of four different preoperative imaging workups (IWs) for prediction of lymph node metastases (LNMs) in endometrial cancer (EC): pelvic MRI alone (IW1), MRI and [18F]FDG-PET/CT in all patients (IW2), MRI with selective [18F]FDG-PET/CT if high-risk preoperative histology (IW3), and MRI with selective [18F]FDG-PET/CT if MRI indicates FIGO stage ≥ 1B (IW4). Methods In 361 EC patients, preoperative staging parameters from both pelvic MRI and [18F]FDG-PET/CT were recorded. Area under receiver operating characteristic curves (ROC AUC) compared the diagnostic performance for the different imaging parameters and workups for predicting surgicopathological FIGO stage. Survival data were assessed using Kaplan-Meier estimator with log-rank test. Results MRI and [18F]FDG-PET/CT staging parameters yielded similar AUCs for predicting corresponding FIGO staging parameters in low-risk versus high-risk histology groups (p ≥ 0.16). The sensitivities, specificities, and AUCs for LNM prediction were as follows: IW1—33% [9/27], 95% [185/193], and 0.64; IW2—56% [15/27], 90% [174/193], and 0.73 (p = 0.04 vs. IW1); IW3—44% [12/27], 94% [181/193], and 0.69 (p = 0.13 vs. IW1); and IW4—52% [14/27], 91% [176/193], and 0.72 (p = 0.06 vs. IW1). IW3 and IW4 selected 34% [121/361] and 54% [194/361] to [18F]FDG-PET/CT, respectively. Employing IW4 identified three distinct patient risk groups that exhibited increasing FIGO stage (p < 0.001) and stepwise reductions in survival (p ≤ 0.002). Conclusion Selective [18F]FDG-PET/CT in patients with high-risk MRI findings yields better detection of LNM than MRI alone, and similar diagnostic performance to that of MRI and [18F]FDG-PET/CT in all.publishedVersio

Cancer awareness in the general population varies with sex, age and media coverage: A population-based survey with focus on gynecologic cancers

Objectives There is a need for more knowledge about the public awareness and attitudes towards gynecologic cancers. We employed a research-purpose population-based citizen panel to assess how often people recall gynecologic cancers compared to other cancer types and to explore the relative importance of different information channels in relaying cancer information. Study design We conducted an online survey using the Norwegian Citizen Panel (n = 1441 respondents), exploring associations between demographic factors and frequency of mentioning specific cancer types. We also searched The Norwegian Media Archive to assess the media coverage of different cancer types. Factors affecting likelihood of mentioning different cancers were assessed by multivariate regression. Results Only 41 % of respondents listed one or more cancers in female genital organs. Of the gynecological cancers, cervical cancer was most frequently mentioned (28 %), followed by ovarian (12 %) and endometrial cancer (11 %). Female responders were more likely to mention cervical (OR 2.47, 95 % CI 2.16–2.78) and ovarian cancer (OR 2.09, 95 % CI 1.60–2.58) than male responders, but not endometrial cancer. Family and friends who have had cancer (50 %) and different types of media coverage (41 %) were reported as the most common sources of cancer information. The three most frequently mentioned cancer types in our survey were breast (77 %), hematologic (76 %) and lung cancer (75 %), which also were the cancer types having most media coverage. Conclusions Gynecological cancers are less frequently mentioned by Norwegian citizens when compared to several other cancer types such as breast-, hematologic- and lung cancer. Sex and age are important factors that affect awareness of cancer types. Media is likely to play an important role in what cancer types the public recalls

Blood steroid levels predict survival in endometrial cancer and reflect tumor estrogen signaling

Objective Blood-based biomarkers are attractive due to ease of sampling and standardized measurement technology, reducing obstacles to clinical implementation. The objective of this study was to evaluate a clinically available method of steroid hormone measurement for its prognostic potential in endometrial cancer. Methods We quantified seven steroid hormones by liquid chromatography-tandem mass spectrometry in 100 endometrial cancer patients from a prospective cohort. Abdominal fat distribution was assessed from abdominal computed tomography (CT) scans. Steroid hormone levels were compared to clinical characteristics, fat distribution and gene expression in primary tumor samples. Results Low levels of 17OH-progesterone, 11-deoxycortisol and androstenedione were associated with aggressive tumor characteristics and poor disease specific survival (p = .003, p = .001 and p = .02 respectively). Adjusting for preoperative risk based on histological type and grade, low 17OH-progesterone and 11-deoxycortisol independently predicted poor outcome with hazard ratios of 2.69 (p = .033, 95%CI: 1.09–6.68) and 3.40 (p = .020, 1.21–9.51), respectively. Tumors from patients with low steroid level displayed increased expression of genes related to mitosis and cell cycle progression, whereas high steroid level was associated with upregulated estrogen signaling and genes associated with inflammation. Estrone and estradiol correlated to abdominal fat volume in all compartments (total, visceral, subcutaneous, p < .001 for all), but not to the visceral fat proportion. Patients with higher levels of circulating estrogens had increased expression of estrogen signaling related genes. Conclusion Low levels of certain endogenous steroids are associated with aggressive tumor traits and poor survival and may provide preoperative information independent of histological biomarkers already in use.publishedVersio

Blood steroid levels predict survival in endometrial cancer and reflect tumor estrogen signaling

Objective Blood-based biomarkers are attractive due to ease of sampling and standardized measurement technology, reducing obstacles to clinical implementation. The objective of this study was to evaluate a clinically available method of steroid hormone measurement for its prognostic potential in endometrial cancer. Methods We quantified seven steroid hormones by liquid chromatography-tandem mass spectrometry in 100 endometrial cancer patients from a prospective cohort. Abdominal fat distribution was assessed from abdominal computed tomography (CT) scans. Steroid hormone levels were compared to clinical characteristics, fat distribution and gene expression in primary tumor samples. Results Low levels of 17OH-progesterone, 11-deoxycortisol and androstenedione were associated with aggressive tumor characteristics and poor disease specific survival (p = .003, p = .001 and p = .02 respectively). Adjusting for preoperative risk based on histological type and grade, low 17OH-progesterone and 11-deoxycortisol independently predicted poor outcome with hazard ratios of 2.69 (p = .033, 95%CI: 1.09–6.68) and 3.40 (p = .020, 1.21–9.51), respectively. Tumors from patients with low steroid level displayed increased expression of genes related to mitosis and cell cycle progression, whereas high steroid level was associated with upregulated estrogen signaling and genes associated with inflammation. Estrone and estradiol correlated to abdominal fat volume in all compartments (total, visceral, subcutaneous, p < .001 for all), but not to the visceral fat proportion. Patients with higher levels of circulating estrogens had increased expression of estrogen signaling related genes. Conclusion Low levels of certain endogenous steroids are associated with aggressive tumor traits and poor survival and may provide preoperative information independent of histological biomarkers already in use

What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

Background: Tumor size assessment by MRI is central for staging uterine cervical cancer. However, the optimal role of MRI-derived tumor measurements for prognostication is still unclear. Material and methods: This retrospective cohort study included 416 women (median age: 43 years) diagnosed with cervical cancer during 2002–2017 who underwent pretreatment pelvic MRI. The MRIs were independently read by three radiologists, measuring maximum tumor diameters in three orthogonal planes and maximum diameter irrespective of plane (MAXimaging). Inter-reader agreement for tumor size measurements was assessed by intraclass correlation coefficients (ICCs). Size was analyzed in relation to age, International Federation of Gynecology and Obstetrics (FIGO) (2018) stage, histopathological markers, and disease-specific survival using Kaplan–Meier-, Cox regression-, and time-dependent receiver operating characteristics (tdROC) analyses. Results: All MRI tumor size variables (cm) yielded high areas under the tdROC curves (AUCs) for predicting survival (AUC 0.81–0.84) at 5 years after diagnosis and predicted outcome (hazard ratios [HRs] of 1.42–1.76, p < 0.001 for all). Only MAXimaging independently predicted survival (HR = 1.51, p = 0.03) in the model including all size variables. The optimal cutoff for maximum tumor diameter (≥ 4.0 cm) yielded sensitivity (specificity) of 83% (73%) for predicting disease-specific death after 5 years. Inter-reader agreement for MRI-based primary tumor size measurements was excellent, with ICCs of 0.83–0.85. Conclusion: Among all MRI-derived tumor size measurements, MAXimaging was the only independent predictor of survival. MAXimaging ≥ 4.0 cm represents the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. Inter-reader agreement for MRI-based tumor size measurements was excellent

Interobserver agreement and prognostic impact for MRI–based 2018 FIGO staging parameters in uterine cervical cancer

Objectives To evaluate the interobserver agreement for MRI–based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers. Methods This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI–derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan–Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics. Results Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI–derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI–based staging parameters improved risk stratification when compared to corresponding clinical assessments alone. Conclusion The interobserver agreement for central MRI–derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer

Visceral fat percentage for prediction of outcome in uterine cervical cancer

Objective The prognostic role of adiposity in uterine cervical cancer (CC) is largely unknown. Abdominal fat distribution may better reflect obesity than body mass index. This study aims to describe computed tomography (CT)-assessed abdominal fat distribution in relation to clinicopathologic characteristics, survival, and tumor gene expression in CC. Methods The study included 316 CC patients diagnosed during 2004–2017 who had pre-treatment abdominal CT. CT-based 3D segmentation of total-, subcutaneous- and visceral abdominal fat volumes (TAV, SAV and VAV) allowed for calculation of visceral fat percentage (VAV% = VAV/TAV). Liver density (LD) and waist circumference (at L3/L4-level) were also measured. Associations between CT-derived adiposity markers, clinicopathologic characteristics and disease-specific survival (DSS) were explored. Gene set enrichment of primary tumors were examined in relation to fat distribution in a subset of 108 CC patients. Results High TAV, VAV and VAV% and low LD were associated with higher age (≥44 yrs.; p ≤ 0.017) and high International Federation of Gynecology and Obstetrics (FIGO) (2018) stage (p ≤ 0.01). High VAV% was the only CT-marker predicting high-grade histology (p = 0.028), large tumor size (p = 0.016) and poor DSS (HR 1.07, p < 0.001). Patients with high VAV% had CC tumors that exhibited increased inflammatory signaling (false discovery rate [FDR] < 5%). Conclusions High VAV% is associated with high-risk clinical features and predicts reduced DSS in CC patients. Furthermore, patients with high VAV% had upregulated inflammatory tumor signaling, suggesting that the metabolic environment induced by visceral adiposity contributes to tumor progression in CC.publishedVersio

Risk stratification of endometrial cancer patients: FIGO stage, biomarkers and molecular classification

Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives