Conditional Survival of female patients with operable invasive Breast Cancer in US: A population-based study

Conditional Risks of Biochemical Failure and Prostate Cancer-Specific Death in Patients Undergoing External Beam Radiotherapy: A Secondary Analysis of 2 Randomized Clinical Trials

Importance

As patients achieve years of survival after treatment for prostate cancer, the risk of biochemical failure (BF) or prostate cancer-specific death (PCSD) may evolve over time, with clinical relevance to both patients and clinicians.

Objective

To determine conditional BF-free survival, PSCD, and overall survival estimates for patients with low- or intermediate-risk prostate cancer enrolled in the Radiation Therapy Oncology Group (RTOG) 0126 and RTOG 0415 clinical trials. A secondary objective was to determine whether prognostic factors at diagnosis remain relevant at later points in follow-up.

Design, Setting, and Participants

A pooled secondary analysis of patients treated with external-beam radiotherapy alone and enrolled in the prospective randomized clinical trials RTOG 0126 and RTOG 0415 was performed. Patients included for analysis were enrolled between March 2002 and December 2009 with a median follow-up of 6.9 years. Overall survival was calculated using the Kaplan-Meier method at various survivorship time points. Cumulative incidence was used to calculate BF rates using the Phoenix definition, as well as PCSD. Risk factors such as Gleason score, tumor (T) stage, prostate-specific antigen level, and the equivalent dose in 2 Gy fractions of prescribed dose were analyzed at different time points using multivariable Cox proportional hazards modeling. Data were analyzed from November 2021 to February 2023.

Main Outcomes and Measures

Conditional risks of BF and PCSD after completion of external-beam radiotherapy.

Results

A total of 2591 patients (median [IQR] age, 69 [63-73] years) were included in the study with a mean (range) PSA level of 7.1 (4.7-8.9) ng/mL, 1334 patients (51.5%) with a Gleason score 6 disease, and 1706 patients (65.8%) with T1 disease. Rates of BF from time of treatment were 1.63% (95% CI, 1.20%-2.18%) at 1 year, 7.04% (95% CI, 6.09%-8.08%) at 3 years, 12.54% (95% CI, 11.28%-13.88%) at 5 years, and 22.32% (95% CI, 20.46%-24.24%) at 8 years. For patients surviving 1, 3, and 5 years without BF, the rates of BF in the next 5 years were 14.20% (95% CI, 12.80%-15.66%), 17.19% (95% CI, 15.34%-19.14%), and 18.85% (95% CI, 16.21%-21.64%), respectively. At the initial time point, the rate of PCSD in the next 5 years was 0.66% (95% CI, 0.39%-1.04%). For patients who achieved 1, 3, 5, and 8 years of survivorship, the rates of PCSD in the next 5 years were 1.16% (95% CI, 0.77-1.67) at 1 year, 2.42% (95% CI, 1.74%-3.27%) at 3 years, 2.88% (95% CI, 2.01%-3.99%) at 5 years, and 3.49% (95% CI, 0.98%-8.73%) at 8 years.

Conclusions and Relevance

In this secondary analysis of 2 randomized clinical trials of patients undergoing external beam radiotherapy for prostate cancer, the conditional risks of BF and death from prostate cancer increased with time for patients with low- and intermediate-risk prostate cancer treated with radiotherapy alone. These results could inform optimal trial design and may be helpful information for patients evaluated in follow-up.

Trial Registration

ClinicalTrials.gov Identifier: NCT00033631; NCT00331773.

Methods for Inclusive Underwriting of Breast Cancer Risk with Machine Learning and Innovative Algorithms

INTRODUCTION

-Due to early detection and improved therapies, the prevalence of long-term breast cancer survivors is increasing. This has increased the need for more inclusive underwriting in individuals with a history of breast cancer. Herein, we developed a method using algorithm aiming facilitating the underwriting of multiple parameters in breast cancer survivors.

METHODS

-Variables and data were extracted from the SEER database and analyzed using 4 different machine learning based algorithms (Logistic Regression, GA2M, Random Forest, and XGBoost) that were compared with Kaplan Meier survival estimates. The performances of these algorithms have been compared with multiple metrics (Log Loss, AUC, and SMR). In situ (non-invasive) and metastatic breast cancer were excluded from this analysis.

RESULTS

-Parameters included the pathological subtype, pTNM staging (T: tumor size, N; number of nodes; M presence or absence of metastases), Scarff-Bloom-Richardson grading, the expression of estrogen and progesterone hormone receptors were selected to predict the individual outcome at any time point from diagnosis. While all models had identical performance in terms of statistical metrics (AUC, Log Loss, and SMR), the logistic regression was the one and only model that respects all business constraints and was intelligible for medical and underwriting users.

CONCLUSION

-This study provides insight to develop algorithms to set underwriter-friendly calculators for more accurate risk estimations that can be used to rationalize insurance pricing for breast cancer survivors. This study supports the development of a more inclusive underwriting based on models that can encompass the heterogeneity of several malignancies such as breast cancer.

Breast cancer mortality in 500 000 women with early invasive breast cancer diagnosed in England, 1993-2015: population based observational cohort study

OBJECTIVES

To describe long term breast cancer mortality among women with a diagnosis of breast cancer in the past and estimate absolute breast cancer mortality risks for groups of patients with a recent diagnosis.

DESIGN

Population based observational cohort study.

SETTING

Routinely collected data from the National Cancer Registration and Analysis Service.

PARTICIPANTS

All 512 447 women registered with early invasive breast cancer (involving only breast and possibly axillary nodes) in England during January 1993 to December 2015, with follow-up to December 2020.

MAIN OUTCOME MEASURES

Annual breast cancer mortality rates and cumulative risks by time since diagnosis, calendar period of diagnosis, and nine characteristics of patients and tumours.

RESULTS

For women with a diagnosis made within each of the calendar periods 1993-99, 2000-04, 2005-09, and 2010-15, the crude annual breast cancer mortality rate was highest during the five years after diagnosis and then declined. For any given time since diagnosis, crude annual breast cancer mortality rates and risks decreased with increasing calendar period. Crude five year breast cancer mortality risk was 14.4% (95% confidence interval 14.2% to 14.6%) for women with a diagnosis made during 1993-99 and 4.9% (4.8% to 5.0%) for women with a diagnosis made during 2010-15. Adjusted annual breast cancer mortality rates also decreased with increasing calendar period in nearly every patient group, by a factor of about three in oestrogen receptor positive disease and about two in oestrogen receptor negative disease. Considering just the women with a diagnosis made during 2010-15, cumulative five year breast cancer mortality risk varied substantially between women with different characteristics: it was <3% for 62.8% (96 085/153 006) of women but ≥20% for 4.6% (6962/153 006) of women.

CONCLUSIONS

These five year breast cancer mortality risks for patients with a recent diagnosis may be used to estimate breast cancer mortality risks for patients today. The prognosis for women with early invasive breast cancer has improved substantially since the 1990s. Most can expect to become long term cancer survivors, although for a few the risk remains appreciable.

Conditional Cancer-Specific Survival for Inflammatory Breast Cancer: Analysis of SEER, 2010 to 2016

BACKGROUND

Conditional survival takes into account the time that has elapsed since diagnosis and may have additional informative value. Compared with the static traditional survival evaluation method, conditional survival predictions can be adapted to incorporate the dynamic changes during the disease and provide a more suitable way of identifying time-evolved prognoses.

METHODS

Of 3333 patients diagnosed with inflammatory breast cancer between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Results database. The trend of the hazard rate over time was represented by the kernel density smoothing curve. The traditional cancer-specific survival (CSS) rate was estimated by the Kaplan-Meier method. Conditional CSS assessment was defined as the probability that a patient will survive y years given the x years who already survived after diagnosis, and the formula is as follows: CS(y)=CSS(x + y)/CSS(x). 3-year cancer-specific survival (CSS3) and 3-year conditional cancer-specific survival (CS3) were estimated. The Fine-Gray proportional subdistribution hazard model was constructed to screen for time-dependent risk factors associated with cancer-specific death. Subsequently, a nomogram was applied to predict a 5-year survival rate based on the number of years already survived.

RESULTS

Of 3333 patients, the cancer-specific survival (CSS) rate decreased from 57% in the 4th year to 49% in the 6th year, while the comparable 3-year CS (CS3) rate improved from 65% in the first year to 76% in the third year. Overall, the CS3 rate was superior to actuarial cancer-specific survival, which was also found in subgroup analysis, especially in patients with high-risk characteristics. The Fine-Gray's model indicated that remote organ metastasis (M stage), lymph node metastasis (N stage), and surgery all significantly impacted the prognosis for cancer-specific survival. The Fine-Gray's model-based nomogram was constructed to predict 5-year cancer-specific survival immediately after diagnosis and given survival for 1, 2, 3, and 4 years after diagnosis.

CONCLUSION

High-risk patients had a significantly improved cancer-specific survival prognosis after surviving for 1 or more years after diagnosis with inflammatory breast cancer. The probability of reaching 5-year cancer-specific survival following diagnosis improves with each additional year survived. More effective follow-up is required for patients diagnosed at an advanced N stage, remote organ metastasis, or not received surgery. Additionally, a nomogram and web-based calculator may be helpful for patients with inflammatory breast cancer during follow-up counseling (https://ibccondsurv.shinyapps.io/dynnomapp/).

10-year survival in female breast cancer patients according to ER, PR and HER2 expression: a cancer registry population-based analysis

INTRODUCTION

Invasive breast cancer prognosis has significantly improved over time; however, there are few data about the long-term survival.

MATERIALS AND METHODS

We analysed the data on female breast cancer incident during 2004-2005 in the area of the Tuscan Cancer Registry, distinguishing them in five subtypes, according to ER, PgR, HER2, and Ki67 expression: luminal A, luminal B, luminal B/HER2 + , triple-negative, and HER2 + . Effects of subtypes and age on 10 years breast cancer specific survival were analysed by Kaplan-Meier and multivariate Cox analysis.

RESULTS

The majority of breast cancer were luminal B (57%), and 45% of them were diagnosed at pathological stage I. The 10-year survival rates (p < 0.001) were higher among luminal A (90.2%) and lower among HER-2 + patients (70.3%). Prognostic effect of age was statistically significant (p < 0.0004): the 10-year cancer specific survival rates were higher among 40-59 years of age patients (88.5%), lower among 0-39 (75.8%). Luminal A breast cancer patients had a constant low risk throughout 10 years of follow up, while luminal B/HER2 + and triple negative tumours showed a peak 5 years after the diagnosis and then declined.

DISCUSSION

Our study confirmed the prognostic effect of biological subtype also in a long term follow up study; moreover, age at diagnosis showed to influence the outcome, other than stage at diagnosis and treatment. The long term follow up showed a constant risk of death for luminal A and B tumours, whereas for non-luminal cancer a peak 5 years after the diagnosis was found.

Correlation Analysis of Pathological Features and Axillary Lymph Node Metastasis in Patients with Invasive Breast Cancer

Objective

To investigate the risk factors of axillary lymph node metastasis in patients with invasive breast cancer.

Methods

This study retrospectively included 122 cases of invasive breast cancer patients admitted to the First Medical Center of PLA General Hospital from January 2019 to September 2020. According to postoperative pathological results, axillary lymph node metastasis was divided into axillary lymph node metastasis (ALNM) group (n =40) and non-axillary lymph node metastasis (NALNM) group (n =82). General demographic information was collected and compared between the two groups. Collected pathological results included lymphovascular invasion (LVI) and the expression of estrogen receptor (ER), progestogen receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 detected by immunohistochemistry. Imaging parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) including apparent diffusion coefficient (ADC), early enhanced rate, and time-intensity curve (TIC) were also included into univariate analysis. The variables with differences between the two groups were compared by univariate analysis, and the related factors of axillary lymph node metastasis were analyzed by logistic regression model.

Results

There was no significant difference in general demographic information between the two groups. No significant differences were found in the positive rates of HER-2, ER, PR, Ki-67, pathological types, and clavicular lymph node metastasis and skin chest wall invasion between the two groups (P > 0.05). The proportion of LVI in ALNM group was significantly higher than that in NALNM group (37.50% vs. 6.10%, P < 0.001). The proportion of breast cancer on the left side in the ALNM group was higher than that in the NALNM group, and the difference was statistically significant (70.00% vs. 47.56%, P = 0.019). There were no significant differences in the imaging parameters obtained by DCE-MRI between the two groups. Binary logistics regression analysis showed that LVI (OR =12.258, 95% CI =3.681-40.812, P < 0.001) and left breast cancer (OR =3.598, 95% CI =1.404-9.219, P = 0.008) were risk factors for axillary lymph node metastasis in patients with invasive breast cancer.

Conclusion

The formation of vascular tumor thrombi in breast cancer tissue and left breast cancer are risk factors for axillary lymph node metastasis in invasive breast cancer and might be helpful for preoperative detailed assessment of the patient's condition.

Conditional cause-specific survival after chemotherapy and local treatment for primary stage IV breast cancer: A population-based study

Background

Conditional survival (CS) represents the probability of surviving for additional years after the patient has survived for several years, dynamically describing the survival rate of the patient with the varying time of survival. The aim of this study was to evaluate the conditional cause-specific survival (CCSS) after chemotherapy and local treatment for metastatic breast cancer, and to identify the prognostic factors affecting the CCSS.

Methods

Patients diagnosed with primary stage IV breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 were included. CS is defined as the probability of additional survival for y years after the patient had survived x years with the calculation formula CCSS (x | y) = CSS (x + y)/CSS (x), where CSS(x) indicates the patient’s cause-specific survival rate at the time of x years. Cox proportional hazard models were used to evaluate predictors of CCSS.

Results

A total of 3,194 patients were included. The 5-year CSS was 39%, whereas the 5-year CCSS increased to 46%, 57%, 71%, and 85% after the diagnosis of 1, 2, 3, and 4 years. For patients with adverse clinical pathological features, CCSS had more pronounced increase with survival time and is more different from the CSS at diagnosis. No matter at the time of diagnosis or 1 year or 3 years after diagnosis, HER2 status, local treatment, and multisite metastasis were independent prognostic factors that affect the long-term survival of patients (all P &lt; 0.05).

Conclusion

The 5-year CCSS of patients with stage IV breast cancer was extended as the survival years increased. HER2 status, multisite metastasis, and local treatment were independent prognostic factors even 3 years after diagnosis.

Conditional survival for high-risk early-stage cervical cancer patients with lymph node metastasis after hysterectomy

BACKGROUND

To estimate conditional survival (CS) for high-risk early-stage cervical cancer patients with lymph node metastasis after hysterectomy.

METHODS

1964 T_1-2N₁M₀ cervical cancer patients who underwent primary hysterectomy from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Result (SEER) Program. Univariate and multivariate cox regression analysis were used to identify independent risk factors. 5-year conditional disease-specific survival (CDS5) and 5-year conditional relative survival (CRS5) were estimated. CDS5 and CRS5 stratified by risk factors were further calculated.

RESULTS

CDS5 and CRS5 increased from 71.0% and 73.7% at 0-year to 89.2% and 91.7% at 5-year, respectively. Inversely, the actuarial disease-specific survival and RS dropped from 71.0% and 73.7% at 5-year to 63.3% and 67.6% at 10-year, respectively. Patients with unfavorable factors had a bigger gap between actuarial survival and CS. Both CDS5 and CRS5 curves across stratas of each prognostic factor had a tendency to level off with time elapsing. Notably, CRS5 couldn't exceed 95% even after 5-year follow-up except for patients with grade I disease (CRS5 at 5-year: 100%) or tumor size less than 2 cm (CRS5 at 5-year: 96%).

CONCLUSION

CS increased over time while actuarial survival decreased as time passed. Patients with unfavorable factors had bigger improvement in CS than those with favorable factors. Excess mortality still existed in these patients after 5-year follow-up compared to the general population except for patients with grade I disease or tumor size <2 cm, who might gradually decrease follow-up times after 5-year.