Assessment of the prognostic and discriminating value of the novel bioscore system for breast cancer; a SEER database analysis

Relative Burden of Cancer and Noncancer Mortality Among Long-Term Survivors of Breast, Prostate, and Colorectal Cancer in the US

Importance

Improvements in cancer outcomes have led to a need to better understand long-term oncologic and nononcologic outcomes and quantify cancer-specific vs noncancer-specific mortality risks among long-term survivors.

Objective

To assess absolute and relative cancer-specific vs noncancer-specific mortality rates among long-term survivors of cancer, as well as associated risk factors.

Design, Setting, and Participants

This cohort study included 627 702 patients in the Surveillance, Epidemiology, and End Results cancer registry with breast, prostate, or colorectal cancer who received a diagnosis between January 1, 2003, and December 31, 2014, who received definitive treatment for localized disease and who were alive 5 years after their initial diagnosis (ie, long-term survivors of cancer). Statistical analysis was conducted from November 2022 to January 2023.

Main Outcomes and Measures

Survival time ratios (TRs) were calculated using accelerated failure time models, and the primary outcome of interest examined was death from index cancer vs alternative (nonindex cancer) mortality across breast, prostate, colon, and rectal cancer cohorts. Secondary outcomes included subgroup mortality in cancer-specific risk groups, categorized based on prognostic factors, and proportion of deaths due to cancer-specific vs noncancer-specific causes. Independent variables included age, sex, race and ethnicity, income, residence, stage, grade, estrogen receptor status, progesterone receptor status, prostate-specific antigen level, and Gleason score. Follow-up ended in 2019.

Results

The study included 627 702 patients (mean [SD] age, 61.1 [12.3] years; 434 848 women [69.3%]): 364 230 with breast cancer, 118 839 with prostate cancer, and 144 633 with colorectal cancer who survived 5 years or more from an initial diagnosis of early-stage cancer. Factors associated with shorter median cancer-specific survival included stage III disease for breast cancer (TR, 0.54; 95% CI, 0.53-0.55) and colorectal cancer (colon: TR, 0.60; 95% CI, 0.58-0.62; rectal: TR, 0.71; 95% CI, 0.69-0.74), as well as a Gleason score of 8 or higher for prostate cancer (TR, 0.61; 95% CI, 0.58-0.63). For all cancer cohorts, patients at low risk had at least a 3-fold higher noncancer-specific mortality compared with cancer-specific mortality at 10 years of diagnosis. Patients at high risk had a higher cumulative incidence of cancer-specific mortality than noncancer-specific mortality in all cancer cohorts except prostate.

Conclusions and Relevance

This study is the first to date to examine competing oncologic and nononcologic risks focusing on long-term adult survivors of cancer. Knowledge of the relative risks facing long-term survivors may help provide pragmatic guidance to patients and clinicians regarding the importance of ongoing primary and oncologic-focused care.

Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer

PURPOSE

The combination of anatomical and biological factors of breast cancer in a new staging system has a prognostic role. This study investigates the prognostic value of the Bioscore among patients with breast cancer with respect to disease-free survival (DFS).

MATERIAL AND METHODS

This study included 317 patients with breast cancer who were identified between January 2015 and December 2018 at Clinical Oncology Department of Assiut University Hospital. Their cancer baseline characteristics were recorded: pathologic stage (PS), T stage (T), nodal stage (N), grade (G), estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) status. Univariate and two multivariate analyses were performed to identify which of these variables are associated with DFS. Model performance was quantified using Harrell's concordance index (C-index), and the Akaike information criterion (AIC) was used to compare model fits.

RESULTS

The significant factors in the univariate analysis were PS3, T2, T3, T4, N3, G2, G3, ER-negative, PR-negative, and HER2-negative. In the first multivariate analysis, PS3, G3, and ER-negative were the significant factors, and in the second multivariate analysis, T2, T4, N3, G3, and ER-negative were the significant factors. Two sets of models were built to determine the utility of combining variables. Models incorporating G and ER status had the highest C-index (0.72) for T + N + G + ER in comparison with (0.69) PS + G + ER and the lowest AIC (953.01) for T + N + G + ER and (966.9) for PS + G + ER.

CONCLUSION

Using the Bioscore in breast cancer staging helps to identify patients at increased risk of recurrence. It provides more optimistic prognostic stratification than the anatomical staging alone for DFS.

Expanding the Staging Criteria for T1-2N0 Hormone-Receptor Positive Breast Cancer Patients Enrolled in TAILORx

BACKGROUND

The American Joint Committee on Cancer (AJCC) 8th edition pathologic prognostic staging (PPS) incorporates anatomic and biologic factors. The OncotypeDX Breast Recurrence Score (RS) was included based on the initial report of the TAILORx trial, with T1-2N0 hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients who had a RS < 11 staged as PPS 1A. This study examined whether the RS criteria for PPS 1A can be further expanded using patients enrolled in the TAILORx trial.

METHODS

The TAILORx trial enrolled 10,273 HR+HER2- T1-2N0 patients. Those with incomplete HR-status/grade and T3 disease were excluded for analysis. The recurrence-free interval (RFI) was compared between the patients who did and those who did not fall into the current PPS 1A category using the Kaplan-Meier method.

RESULTS

The study enrolled 9535 patients for analysis. The RS was < 11 in 16.1%, 11-17 in 35.9%, 18-25 in 32.4%, and > 25 in 15.6% of the patients. The majority (91.2%) of the patients (including all the T1N0 patients regardless of RS) were PPS 1A, and 8.8% were not-PPS 1A. The median follow-up time was 95 months. The PPS 1A patients had an 8-year RFI of 94.2%, which was similar to that of the patients with a RS of 11-17 who were not-PPS 1A (91.7%; p = 0.07) and better than that of the patients with a RS ≥ 18 who were not-PPS 1A (85.4% for a RS of 18-25, 76.0% for a RS > 25; both p < 0.01). Similar RFI trends were seen in patients who received endocrine therapy or chemotherapy followed by endocrine therapy.

CONCLUSIONS

Patients with T1-2N0 HR+HER2- breast cancer and a RS < 18 have an RFI similar to that of patients staged as PPS 1A by the current AJCC staging system, regardless of treatment, suggesting that the criteria for PPS 1A can be expanded to include a RS < 18.

Molecular Subtypes, Metastatic Pattern and Patient Age in Breast Cancer: An Analysis of Italian Network of Cancer Registries (AIRTUM) Data

Breast cancer stage at diagnosis, patient age and molecular tumor subtype influence disease progression. The aim of this study was to analyze the relationships between these factors and survival in breast cancer patients among the Italian population using data from the AIRTUM national database. We enrolled women with primary breast cancer from 17 population-based cancer registries. Patients were subdivided into older (>69 years), middle (50–69 years) and younger age groups (<50 years) and their primary tumors categorized into four molecular subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. There were 8831 patients diagnosed between 2010 and 2012 included. The most represented age group was 50–69 years (41.7%). In 5735 cases the molecular subtype was identified: HER2–/HR+ was the most frequent (66.2%) and HER2+/HR− the least (6.2%). Of the 390 women with metastases at diagnosis, 38% had simultaneous involvement of multiple sites, independent of age and molecular profile. In women with a single metastatic site, bone (20% of cases), liver (11%), lung (7%) and brain (3%) were the most frequent. In the studied age groups with different receptor expression profiles, the tumor metastasized to target organs with differing frequencies, affecting survival. Five-year survival was lowest in women with triple-negative (HER2−/HR–) tumors and women with brain metastases at diagnosis.

Expanding Criteria for Prognostic Stage IA in Hormone Receptor-Positive Breast Cancer

BACKGROUND

The prognostic significance of patients with low-risk recurrence score (RS) results in the context of the American Joint Committee on Cancer (AJCC) eighth edition pathologic prognostic staging has not been investigated. We evaluated if expanded RS criteria can be considered for downstaging in AJCC pathologic prognostic staging.

METHODS

Using Surveillance, Epidemiology, and End Results data, we identified patients with T1-3N0-3M0 hormone receptor-positive, HER2-negative breast cancer treated from 2010 to 2015 with follow-up data through 2016. We evaluated TNM categories, grade, and RS result. The primary outcome measured was 5-year disease-specific survival (DSS) of patients with low-risk RS results not already pathologic prognostic stage IA, determined by T and N categories per AJCC eighth edition. All statistical tests were 2-sided.

RESULTS

Of 154 050 patients with median follow-up of 49 months (range = 0-83), RS results were obtained in 60 886 (39.5%): RS was less than 11 in 13 570 (22.3%); 11-17 in 22 719 (37.3%); 18-25 in 16 521 (27.1%); and 26 or higher in 8076 (13.3%). Five-year DSS for pathologic prognostic stage IA patients (n = 114 910, 74.6%) was 98.8%. Among N0-1 patients with a RS less than 18 not staged as pathologic prognostic stage IA by current criteria, 5-year DSS was excellent and not statistically significantly different than for pathologic prognostic stage IA patients (97.2%-99.7%; P > .05). For those with a RS of 18-25, there was a small decrease in DSS for T2N0 (2.3%) and modest decrease for T1-2N1 (4.2%-6.4%) compared with pathologic prognostic stage IA patients (P < .001).

CONCLUSION

Patients with a RS less than 18 have excellent 5-year DSS regardless of T category for N0-1 disease suggesting further modification of the AJCC staging system using this cutoff.

Comparison of Breast Cancer Staging Systems After Neoadjuvant Chemotherapy

BACKGROUND

No consensus exists for optimal staging following neoadjuvant chemotherapy (NAC). We compared the performance of the American Joint Committee on Cancer (AJCC) pathologic prognostic staging system, Residual Cancer Burden (RCB) Index, and the Neo-Bioscore in breast cancer patients after NAC.

METHODS

Patients with stage I-III breast cancer who received NAC at Dana-Farber Cancer Institute from 2004 to 2014 were identified. Kaplan-Meier curves were used to estimate disease-free survival (DFS) and overall survival (OS), and model fits were compared by receiver operator characteristic (ROC) curve using the c-statistic and DeLong's test.

RESULTS

Overall, 802 patients with a median age of 48 years received NAC. Most patients presented with cT2 (n = 470, 58.6%) and cN1 (n = 422, 52.6%) disease. The subtype was estrogen receptor (ER)- and/or progesterone receptor (PR)-positive/human epidermal growth factor receptor 2 (HER2)-negative in 296 (36.9%) patients, HER2-positive in 261 (32.5%) patients, and triple-negative in 245 (30.5%) patients. Median follow-up was 79.5 months. There were 174 recurrences (30 local, 25 regional, 145 distant), with 676 (76.8%) patients alive at last follow-up. AJCC pathologic prognostic staging and RCB had better discrimination for estimated 7-year DFS and OS compared with the Neo-Bioscore. The ROC c-statistics for DFS model fit were similar for AJCC pathologic prognostic stage (0.72) and RCB (0.71, p = non-significant); both had improved model fit versus the Neo-Bioscore (0.65, p < 0.01). The c-statistics for OS were 0.74, 0.71, and 0.70 for AJCC pathologic prognostic stage, RCB, and Neo-Bioscore, respectively (p = non-significant).

CONCLUSIONS

These results validate the ability of these staging systems to stratify survival outcomes in NAC patients, with best discrimination achieved using AJCC pathologic prognostic stage or RCB.

Evaluating overall survival and competing risks of survival in patients with early-stage breast cancer using a comprehensive nomogram

BACKGROUND

Patients with early-stage breast cancer (BC) live long but have competing comorbidities. This study aimed to estimate the effect of cancer and other causes of death in patients with early-stage BC and further quantify the survival differences.

MATERIALS AND METHODS

Data of patients diagnosed with BC between 2010 and 2016 were collected from the Surveillance, Epidemiology, and End Results database. The cumulative incidence function for breast cancer-specific mortality (BCSM) and other cause-specific mortality (OCSM) was estimated, and the differences were tested using the Gray test. The nomogram for estimating 3-, 4-, and 5-year overall survival (OS), breast cancer-specific survival, and other cause-specific survival was established based on Cox regression analysis and Fine and Gray competing risk analysis. The discriminative ability, calibration, and precision of the nomogram were evaluated and compared using C statistics, calibration plots, and area under the receiver operating characteristic curve.

RESULTS

A total of 196 304 eligible patients with early-stage BC were identified in this study. Of these, 12 417 (6.3%) patients died: 5628 (45.3%) due to BC and 6789 (54.7%) due to other causes. Five validated variables were incorporated to develop the prognostic nomogram: age, grade, tumor size, subtype, and surgery of primary site (Figure 3). Age was a strong predictive factor, which was more obvious in OCSM. The effect of surgery was more prominent in BCSM. Increased tumor size was correlated with OS and BCSM and slightly correlated with OCSM. Grade and subtype differences were more predominant in BCSM than in OCSM. The established nomogram was well calibrated and displayed good discrimination.

CONCLUSIONS

We evaluate OS and competing risks of death in patients with early-stage BC, establishing the first comprehensive prognostic nomogram.

Incorporation of clinical and biological factors improves prognostication and reflects contemporary clinical practice

We developed prognostic models for breast cancer-specific survival (BCSS) that consider anatomic stage and other important determinants of prognosis and survival in breast cancer, such as age, grade, and receptor-based subtypes with the intention to demonstrate that these factors, conditional on stage, improve prediction of BCSS. A total of 20,928 patients with stage I–III invasive primary breast cancer treated at The University of Texas MD Anderson Cancer Center between 1990 and 2016, who received surgery as an initial treatment were identified to generate prognostic models by Fine-Gray competing risk regression model. Model predictive accuracy was assessed using Harrell’s C-index. The Aalen–Johansen estimator and a selected Fine–Gray model were used to estimate the 5-year and 10-year BCSS probabilities. The performance of the selected model was evaluated by assessing discrimination and prediction calibration in an external validation dataset of 29,727 patients from the National Comprehensive Cancer Network (NCCN). The inclusion of age, grade, and receptor-based subtype in addition to stage significantly improved the model predictive accuracy (C-index: 0.774 (95% CI 0.755–0.794) vs. 0.692 for stage alone, p < 0.0001). Young age (<40), higher grade, and TNBC subtype were significantly associated with worse BCSS. The selected model showed good discriminative ability but poor calibration when applied to the validation data. After recalibration, the predictions showed good calibration in the training and validation data. More refined BCSS prediction is possible through a model that has been externally validated and includes clinical and biological factors.

Comparative Analysis of Proposed Strategies for Incorporating Biologic Factors into Breast Cancer Staging

BACKGROUND

Tumor biology is an important prognostic factor in breast cancer. This study aimed to compare three staging systems incorporating both biologic factors and anatomic staging (AJCC 8th-edition pathologic prognostic staging, Bioscore, and Risk Score) in a large population-based cohort.

METHODS

The Surveillance, Epidemiology and End Results program was used to select patients with primary stages 1-4 breast cancer diagnosed in 2010. Patients with inflammatory carcinoma, those with missing data for biologic factors, and those with stages 1-3 disease not treated with surgery were excluded from the study. Estimates of 5-year disease-specific survival (DSS) were calculated using the Kaplan-Meier method. The Harrel concordance index (C-index) and the Akaike Information Criterion were used to compare each model in terms of predicting DSS.

RESULTS

The study included 21,901 patients with a median age of 60 years. The median follow-up period was 52 months. All the staging models stratified DSS, with a stepwise decrease in DSS for each increase in risk category or score. The C-index of each model incorporating biologic factors was higher than the C-index for anatomic staging alone (C-index: 0.832 vs. 0.856 for AJCC pathologic prognostic staging, 0.856 for Bioscore, and 0.864 for Risk Score, all p < 0.001). The staging systems incorporating biologic factors did not differ significantly in terms of model fit.

CONCLUSION

Staging systems incorporating biologic factors perform better than anatomic staging alone. Implementation of the AJCC 8th-edition pathologic prognostic staging was an important initial step in the inclusion of tumor biology in staging. Given its simplicity and ease of use, the Risk Score should be given consideration as an alternative staging system.

The predictive value of the prognostic staging system in the 8th edition of the American Joint Committee on Cancer for triple-negative breast cancer: a SEER population-based analysis

Aim: To examine the stage changes and survival differences among triple-negative breast cancer (TNBC) patients based on the prognostic staging system. Methods: We used the SEER database to identify eligible patients with TNBC diagnosed between 2010 and 2014. Kaplan–Meier curves were drawn for comparison. The primary end point was breast cancer-specific survival. Results: The median follow-up time was 26 months for 19,608 patients. The stages of all TNBC patients increased or remained unchanged during rearrangement from anatomic staging to prognostic staging. Stage IIA, IIIA and IIIC comprised the majority of patients. Several patients did not have prognostic staging. Stage IIIC incorporated six substages that contributed to high heterogeneity. Overall, the Kaplan–Meier curves still showed the favorable differentiation among stages and substages, with the exception of stage IIB and substage IIIA (T2N0, grade 2–3) patients. Conclusion: The prognostic information for breast cancer patients provided by the novel prognostic staging system may be less accurate for TNBC patients in our independent analysis. Moreover, stage IIB and substage IIIA (T2N0, grade 2–3) should possibly undergo further evaluation.

Development and validation of nomograms integrating immune-related genomic signatures with clinicopathologic features to improve prognosis and predictive value of triple-negative breast cancer: A gene expression-based retrospective study

Purpose

Accumulating evidence indicated that triple‐negative breast cancer (TNBC) can stimulate stronger immune responses than other subtypes of breast cancer. We hypothesized that integrating immune‐related genomic signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system.

Methods

Ten signatures that reflect specific immunogenic or immune microenvironmental features of TNBC were identified and re‐analyzed using bioinformatic methods. Then, clinically annotated TNBC (n = 711) with the corresponding expression profiles, which predicted a patient's probability of disease‐free survival (DFS) and overall survival (OS), was pooled to evaluate their prognostic values and establish a clinicopathologic‐genomic nomogram. Three and two immune features were, respectively, selected out of 10 immune features to construct nomogram for DFS and OS prediction based on multivariate backward stepwise Cox regression analyses.

Results

By integrating the above immune expression signatures with prognostic clinicopathologic features, clinicopathologic‐genomic nomograms were cautiously constructed, which showed reasonable prediction accuracies (DFS: HR, 1.79; 95% CI, 1.46‐2.18, P < 0.001; AUC, 0.71; OS: HR, 1.96; 95% CI, 1.54‐2.49; P < 0.001; AUC, 0.73). The nomogram showed low‐risk subgroup had higher immune checkpoint molecules (PD‐L1, PD‐1, CTLA‐4, LAG‐3) expression and benefited from radiotherapy (HR, 0.2, 95% CI, 0.05‐0.89; P = 0.034) rather than chemotherapy (HR, 1.26, 95% CI, 0.66‐2.43; P = 0.485).

Conclusions

These findings offer evidence that immune‐related genomic data provide independent and complementary prognostic information for TNBC, and the nomogram might be a practical predictive tool to identify TNBC patients who would benefit from chemotherapy, radiotherapy, and upcoming popularity of immunotherapy.

M-bioscore: proposing a new statistical model for prognostic factors in metastatic breast cancer patients

AIM

The current study aims to propose and internally validate 'M-bioscore', which is a model to help predict the outcomes of untreated metastatic breast cancer patients.

METHODOLOGY

Surveillance, epidemiology and end results (SEER) database (2010-2013) was accessed. Patients were divided into two groups: a training set and a validation set. Through a Cox proportional model, multivariate analysis for potential prognostic factors was performed. M-bioscore was calculated for all patients. Survival analyses were conducted through Kaplan-Meier analysis/log-rank testing.

RESULTS

A total of 6655 metastatic breast cancer patients were analyzed. In the training set, the following factors were linked to better cancer-specific survival in multivariate analysis: estrogen receptor positivity, isolated distant nodal metastases, progesterone receptor positivity, lower nuclear grade and HER2 neu positivity (p < 0.01). Cancer-specific survival was then assessed according to M-bioscore. Adjusted Cox regression cause-specific hazard (using breast cancer death as the event of interest) was evaluated in the validation cohort. Pairwise hazard ratio comparisons between different scores were significant (p < 0.05) except for the comparison between score 6 and 7. C-index for the validation cohort was 0.665 (Standard error (SE): 0.010; 95% CI: 0.646- 0.685).

CONCLUSION

M-bioscore can predict the outcomes of untreated metastatic breast cancer patients. Validation of external datasets is needed.

Incidence and predictors of 1-year mortality among 9236 breast cancer patients referred for adjuvant chemotherapy

AIM

To evaluate the incidence and predictors of mortality in the first year following randomization among breast cancer patients recruited in five adjuvant chemotherapy clinical trials.

METHODS

This is a pooled analysis of 9236 patients from five clinical trials. Univariate and multivariate logistic regression analyses were conducted to evaluate the impact of relevant clinicopathological factors on early mortality.

RESULTS

Early death rates were 0.1% (11 patients) at 6 months and 0.8% (70 patients) at 1 year. Patients with a documented relapse within 1 year have a higher risk of death within the first year (HR: 74.20, 95% CI: 42.28-130.22) in a multivariate Cox regression model. The following factors were predictive of 1-year mortality in multivariate logistic regression analysis: higher T-stage (p = 0.001), higher N-stage (p = 0.004) and negative hormone receptor status (p < 0.0001).

CONCLUSION

Six-month and 1-year mortality rates are low among breast cancer patients referred for adjuvant chemotherapy within a clinical trial.

Prognostic Validation of the American Joint Committee on Cancer 8th Staging System in 24,014 Korean Patients with Breast Cancer

Purpose

The American Joint Committee on Cancer (AJCC) recently released the breast cancer staging system, 8th edition, which included additional four biologic factors. However, there has been no external validation of the prognostic value of the new stages with different population-based databases.

Methods

To validate the prognostic value of the new staging system in the Asian population, with a focus on Korean patients with breast cancer, we performed a retrospective study with data from the Korean Breast Cancer Society that included 24,014 patients with invasive ductal or lobular carcinoma who underwent surgery between January 2009 and January 2012 in Korea. The proportional differences were evaluated between the anatomic staging system (AJCC 7th edition) and the prognostic staging system (AJCC 8th edition, December 2017 published version). Comparisons of overall survival (OS) and disease-free survival (DFS) with Kaplan-Meier graphs and hazard ratios were also performed.

Results

Our analysis included 24,014 patients (median age, 50 years; range, 20–91 years). Stage I, II, and III disease accounted for 47.6%, 43.5%, and 8.9%, respectively, of anatomic stages and 61.8%, 27.6%, and 10.8%, respectively, of clinical prognostic stages. A total of 6,272 cases (26.1%) were upstaged, 4,656 (19.4%) were downstaged, and 13,086 (54.5%) remained unchanged. OS and DFS decreased in the order from prognostic stages IA to IIIC but did not change among the anatomic stage groups.

Conclusion

Our data suggests that the prognostic staging system provides superior prognostic value to the anatomic staging system in Korean patients with breast cancer.

Patterns of on-treatment cardiac adverse events within three clinical trials of adjuvant anthracycline-based chemotherapy

BACKGROUND

This study aims to assess the patterns of development of on-treatment cardiac side effects among patients with early breast cancer receiving anthracycline-based chemotherapy.

METHODS

This is a pooled analysis of patient-level data of patients with early-stage breast cancer who were recruited into three clinical trials to receive different adjuvant chemotherapy regimens. Univariable and multivariable analyses of factors predicting the development of on-treatment cardiac adverse events were conducted through logistic regression analysis. The following factors were evaluated in the univariable analysis: age, menopausal status, body mass index, T stage, and type of chemotherapy protocol.

RESULTS

Among the studied patients, 226 patients (6.7%) experienced 230 incidents of on-treatment cardiac toxicities. Cardiac ischemia was reported among 8 patients, cardiac dysfunction was reported among 19 patients, arrhythmias were reported in 161 patients and other non-specified forms of cardiac adverse events were reported in 42 patients. In univariable logistic regression, the following parameters were predictive of a higher probability of on-treatment cardiac adverse events (P < 0.05): higher age, higher body mass index and FAC chemotherapy protocol. When these factors were included in the multivariable logistic regression analysis, the following factors were predictive of a higher probability of cardiac adverse events: higher body mass index (P = 0.050) and FAC chemotherapy protocol (P = 0.001).

CONCLUSION

On-treatment cardiac events are not uncommon during adjuvant chemotherapy for early breast cancer. Higher dose of anthracyclines and higher body mass index are associated with a higher risk of on-treatment cardiac events.

Evaluation of the eighth American Joint Committee on Cancer staging system for malignant melanoma of the skin

AIM

To validate the changes among the American Joint Committee on Cancer (AJCC) eighth staging system for cutaneous melanoma.

METHODOLOGY

Surveillance, Epidemiology and End Results database (2004-2014) was queried. Kaplan-Meier survival estimates were evaluated according to both AJCC seventh and eighth systems.

RESULTS

Overall survival was assessed according to the two editions and p-values for overall trend were significant (p < 0.001) for all scenarios. Notably for pathologically staged patients, the mean survival for stage IIC was lower than that for stage IIIA and IIIB. Likewise, among clinically staged patients the mean survival for stage IIC was lower than that for stage III (these findings were identical among both editions).

CONCLUSION

AJCC eighth system holds comparable performance to AJCC seventh system.

Comparison of three prognostic models for predicting cancer-specific survival among patients with gastrointestinal stromal tumors

AIM

To evaluate the predictive value for cancer-specific survival of the models of the American Joint Committee on Cancer (AJCC) stage, NIH and Armed Forces Institute of Pathology (AFIP) among patients with gastrointestinal stromal tumors (GISTs).

METHODS

Surveillance, Epidemiology and End Results database (2010-2014) was accessed. Overall survival analysis and adjusted cancer-specific Cox regression hazard was calculated.

RESULTS

For gastric GISTs, concordance-index according to AJCC was 0.834; according to NIH was 0.833; according to AFIP was 0.836. Concordance-index for nongastric GISTs according to AJCC was 0.800, according to NIH was 0.801 and according to AFIP was 0.799.

CONCLUSION

The performance of the three models is comparable with regards to cancer-specific survival prediction.

Evaluation of the prognostic stage in the 8th edition of the American Joint Committee on Cancer in locally advanced breast cancer: An analysis based on SEER 18 database

BACKGROUND

The new "prognostic stage" in the 8th edition of the American Joint Committee on Cancer (AJCC) incorporated important biologic factors such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), histologic grade and TNM stage into one system. The objective of this study was to evaluate the "prognostic stage" in locally advanced breast cancer (LABC) based on the Surveillance, Epidemiology, and End Results (SEER) 18 database.

METHODS

10053 LABCs diagnosed between 2010 and 2013 were enrolled. TNM stage was based on AJCC 7th edition. Comparisons of biologic factor proportions among stage changes were performed using Pearson's chi-square test. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and log rank testing with pairwise comparisons between different stages was conducted. Cox models were fitted to assess the independent prognostic factors.

RESULTS

The prognostic stage grouped LABC into six stages: IB-IIIC among which IB-IIIA had a relatively better survival. It reassigned 74% LABCs to a different tumor stage. 60.4% cases in grade III and 68.3% cases with triple negative breast cancer were upstaged while 57.1% cases with ER/PR dual positivity were down staged. It was an independent prognostic factor of LABC. There were statistically significant survival differences among stage IB-IIIA, IIIB and IIIC. Among each TNM stage, there were statistically significant survival differences among stage changes.

CONCLUSIONS

The prognostic stage provided accurate prognostic information for LABC compared with anatomic TNM stage. It will lead to accuracy in prognosis prediction and optimal treatment selection, and therefore, better outcomes.

Modified staging system for pulmonary carcinoids on the basis of lung cancer TNM system

BACKGROUND

Pulmonary carcinoids are being staged along the lines of lung cancer American Joint Committee on Cancer (AJCC) staging system. The current study evaluated the prognostic value of a modified staging system for patients with pulmonary carcinoid.

PATIENTS AND METHODS

Surveillance, Epidemiology and End Results (SEER) database (2004-2014) was searched through SEER*Stat program. Through recursive partitioning analysis and subsequent decision tree formation, suggested stages were constructed. Overall survival analyses were performed through Kaplan-Meier analysis. The cancer-specific Cox regression hazard (adjusted for age, gender, race, sub-site and surgery) was calculated and pairwise comparisons of hazard ratios were conducted.

RESULTS

A total of 6395 pulmonary carcinoid patients were recruited in the period from 2004-2014. Pairwise hazard ratio comparisons among different AJCC 8th stages were conducted and all comparisons were non-significant except for stage IIB vs. stage IIIA and stage IIIA vs. stage IIIB. Pairwise hazard ratio comparisons among different modified staging system stages were conducted and all comparisons were significant except for stage III vs. stage IV. C-statistic (using death from pulmonary carcinoid as the dependent variable) for AJCC 8th staging system was: 0.794 (SE 0.013; 95% CI 0.769-0.818); for AJCC 7th staging system was: 0.789 (SE 0.013; 95% CI 0.764-0.815), while c-statistic for the modified staging system was: 0.802 (SE 0.012; 95% CI 0.778-0.827).

CONCLUSION

The proposed modified staging system provided a simpler yet prognostically more relevant classification of pulmonary carcinoids compared to AJCC staging systems (both 7th and 8th editions).

Breast cancer neoplastic seeding in the setting of image-guided needle biopsies of the breast

PURPOSE

To identify clinicopathologic, technical, and imaging features associated with neoplastic seeding (NS) following image-guided needle breast biopsy.

METHODS

We performed an institutional review board-approved retrospective review of patients presenting with a new diagnosis of breast cancer or suspicious breast findings requiring biopsy with subsequent diagnosis of NS. The time from biopsy to NS diagnosis was calculated. Histology, grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER2 status, T category, and N category were recorded. Biopsy guidance method, needle gauge, and number of passes were reviewed in addition to the mammographic and sonographic features of the primary tumors and the NS.

RESULTS

Eight cases of NS were identified in 4010 patients. The mean time from biopsy to NS diagnosis was 60.8 days. The most frequent histology was invasive ductal carcinoma (7/8). Six cases were grade 3 (75.0%). Five primary breast cancers were ER, PR, and HER2 negative (62.5%). Seven patients underwent biopsy with ultrasound guidance. Multiple-insertion, non-coaxial ultrasound-guided core-needle biopsy was done in 6 cases. Mammographic presentation of NS was focal asymmetry (3/7 cases), mass (1/7), calcifications only (1/7), or occult (2/7). Sonographic presentation of NS was most often a mass (7/8) with irregular shape (5/7) and without circumscribed margins (6/7) and was occult in 1 case (1/8). NS distribution was subdermal and intradermal.

CONCLUSION

High-grade, triple-negative breast cancers and multiple-insertion, non-coaxial biopsies may be risk factors for NS. NS should be suspected on the basis of the superficial and linear pattern of disease progression in these patients.