Self-Tuning of Signal Detection Level for Energy Detection-Based Carrier Sense in Low-Power Wide-Area Networks.

Carrier sense allows end devices to improve the communication quality through autonomous decentralization by consuming power. In particular, energy detection-based carrier sense can improve communication quality compared with peak detection-based carrier sense. To improve the trade-off between communication quality and energy consumption in low-power wide-area networks (LPWANs), this study proposes a self-tuning method for the signal detection level of an energy detection-based carrier sense, that is, the carrier sense level in sub-GHz band LPWANs. In the proposed method, the carrier sense level of each end device is determined based on the reception success probability of the acknowledgment packet, such that they become low carrier sense levels for an end device with low probability and high carrier sense levels for an end device with high probability. The proposed method enables autonomous decentralized derivation of the carrier sense level using only existing protocols. Numerical examples show that the proposed method can improve the performance of end devices with a high path loss to a gateway.

An Environment-Aware Adaptive Data-Gathering Method for Packet-Level Index Modulation in LPWA.

Low-power wide-area (LPWA) is a communication technology for the IoT that allows low power consumption and long-range communication. Additionally, packet-level index modulation (PLIM) can transmit additional information using multiple frequency channels and time slots. However, in a competitive radio access environment, where multiple sensors autonomously determine packet transmission, packet collisions occur when transmitting the same information. The packet collisions cause a reduction in the throughput. A method has been proposed to design a mapping table that shows the correspondence between indexes and information using a packet collision minimization criterion. However, the effectiveness of this method depends on how the probability of the occurrence of the information to be transmitted is modeled. We propose an environment-aware adaptive data-gathering method that identifies the location of factors affecting sensor information and constructs a model for the probability of the occurrence of sensor information. The packet collision rate of the environment-aware adaptive data-gathering method was clarified through computer simulations and actual experiments on a 429 MHz LPWA. We confirm that the proposed scheme improves the packet collision rate by 15% in the computer simulation and 30% in the experimental evaluation, respectively.

Three Level Recognition Based on the Average of the Phase Differences in Physical Wireless Parameter Conversion Sensor Networks and Its Effect to Localization with RSSI.

In recent years, there have been increased demands for aggregating sensor information from several sensors owing to the spread of the Internet of Things (IoT). However, packet communication, which is a conventional multiple-access technology, is hindered by packet collisions owing to simultaneous access by sensors and waiting time to avoid packet collisions; this increases the aggregation time. The physical wireless parameter conversion sensor network (PhyC-SN) method, which transmits sensor information corresponding to the carrier wave frequency, facilitates the bulk collection of sensor information, thereby reducing the communication time and achieving a high aggregation success rate. However, when more than one sensor transmits the same frequency simultaneously, the estimation accuracy of the number of accessed sensors deteriorates significantly because of multipath fading. Thus, this study focuses on the phase fluctuation of the received signal caused by the frequency offset inherent to the sensor terminals. Consequently, a new feature for detecting collisions is proposed, which is a case in which two or more sensors transmit simultaneously. Furthermore, a method to identify the existence of 0, 1, 2, or more sensors is established. In addition, we demonstrate the effectiveness of PhyC-SNs in estimating the location of radio transmission sources by utilizing three patterns of 0, 1, and 2 or more transmitting sensors.

Estimation Based on Chirp Modulation for Desired and Interference Power and Channel Occupancy Ratio in LoRa.

In terms of low power consumption and long-range communication-low-power wide-area networks (LPWAN) are suitable for wireless sensor networks. Long-range (LoRa) wireless communication is one of the standards of LPWAN. LoRa shares common frequency spectrum bands with both multiple transmitters, which are the sensors in the LoRa system (and those in the other system). Therefore, co-channel interference (CCI) degrades the packet delivery rate. To avoid CCI, the CCI power and the occurrence probability of CCI in the target channel are estimated, then the sensor decides whether to use the channel and where the occurrence probability of CCI is defined as the channel occupancy ratio (COR). If a large signal power is obtained at the receiver, the received signal can be demodulated because of the capture effect. The desired signal power must also be estimated for the capture effect. In this study, we propose an estimation scheme based on chirp modulation of LoRa under spectrum sharing among other systems. The proposed scheme estimates the desired signal power, CCI power, and COR. From the computer simulation results, we clarify the advantages of the proposed scheme in terms of estimation accuracy and packet delivery rate.

A 95-gene signature stratifies recurrence risk of invasive disease in ER-positive, HER2-negative, node-negative breast cancer with intermediate 21-gene signature recurrence scores.

PURPOSE: A subset of patients with intermediate 21-gene signature assay recurrence score may benefit from adjuvant chemoendocrine therapy, but a predictive strategy is needed to identify such patients. The 95-gene signature assay was tested to stratify patients with intermediate RS into high (95GC-H) and low (95GC-L) groups that were associated with invasive recurrence risk. METHODS: Patients with ER-positive, HER2-negative, node-negative breast cancer and RS 11-25 who underwent definitive surgery and adjuvant endocrine therapy without any cytotoxic agents were included. RNA was extracted from archived formalin-fixed, paraffin-embedded samples, and 95-gene signature was calculated. RESULTS: 206 patients had RS of 11-25 (95GC-L, N = 163; 95GC-H, N = 43). In Cox proportional hazards model, 95GC-H was significantly associated with shorter time to recurrence than was 95GC-L (HR 5.94; 95%CI 1.81-19.53; P = 0.005). The correlation between 95-gene signature and 21-gene signature assay scores was not strong (correlation coefficient r = 0.27), which might suggest that 95-gene signature reflects biological characteristics differing from what 21-gene signature shows. CONCLUSIONS: The 95-gene signature stratifies patients with ER-positive, HER2-negative, node-negative invasive breast cancer and intermediate RS of 11-25 into high and low groups that are associated with recurrence risk of invasive disease. Further retrospective analysis in the prospectively accrued TAILORx population is warranted to confirm that 95-gene signature can identify patients who would benefit from adjuvant chemoendocrine therapy.

Theoretical study on proton diffusivity in Y-doped BaZrO3 with realistic dopant configurations.

We theoretically revisit the proton diffusivity in yttrium-doped barium zirconate (Y-doped BaZrO3) with realistic dopant configurations under processing conditions. In a recent study employing the replica exchange Monte Carlo method, the equilibrium Y configurations at typical sintering temperatures were shown to deviate from the random configuration assumed in earlier theoretical studies. In the present study, we took this observation into account and evaluated the effect of the Y configuration on the proton diffusivity. Using the master equation approach based on local diffusion barriers calculated from first principles, the proton diffusivities under realistic Y configurations were estimated to be higher than those in the random configuration. This is explained by the fact that realistic Y configurations have fewer trap sites with deep potential wells compared to the random configuration due to the isolation trend of Y dopants. In addition, the effects of proton-proton interaction and the abundance of preferential conduction pathways are discussed; it is found that both are relatively minor factors compared to the trap site effect in determining the dependence of the proton diffusivity on the Y configurations.

Prognostic Value of HER2 to CEP17 Ratio on Fluorescence In Situ Hybridization Ratio in Patients with Nonmetastatic HER2-Positive Inflammatory and Noninflammatory Breast Cancer Treated with Neoadjuvant Chemotherapy with or without Trastuzumab.

BACKGROUND: We previously reported that in patients with HER2-positive (HER2+) locally advanced breast cancer treated with neoadjuvant trastuzumab-containing regimens, high HER2 to centromere enumerator probe 17 ratio on fluorescence in situ hybridization (HER2 FISH ratio) was an independent predictor of high pathologic complete response (pCR) rate, which translated into improved recurrence-free survival (RFS). We sought to determine whether high HER2 FISH ratio is a predictor of pCR and prognosis in patients with HER2+ nonmetastatic inflammatory breast cancer (IBC) and non-IBC treated with neoadjuvant chemotherapy with or without trastuzumab. MATERIALS AND METHODS: This study included all patients with histologically proven stage III, HER2+ primary IBC, and non-IBC treated with neoadjuvant chemotherapy with or without trastuzumab and definitive surgery during 1999-2012. Univariate and multivariate logistic regression models were applied to assess the effect of covariates on pCR. Kaplan-Meier estimates with log-rank test were employed for survival analysis. Univariate and multivariate Cox proportional hazards models were used to assess the effect of covariates on RFS and overall survival (OS). RESULTS: The study included 555 patients with stage III, HER+ breast cancer, 181 patients with IBC, and 374 with non-IBC. In the IBC cohort, HER2 FISH ratio was not significantly associated with pCR, RFS, or OS. In the non-IBC cohort, higher HER2 FISH ratio was significantly associated with higher pCR rate and longer OS. CONCLUSION: HER2 FISH ratio showed prognostic value among patients with HER2+ non-IBC but not HER2+ IBC treated with neoadjuvant chemotherapy. This disparity may be due to the underlying aggressive nature of IBC. IMPLICATIONS FOR PRACTICE: The findings of this study indicate that the HER2 to fluorescence in situ hybridization ratio as a continuous variable has promise as a predictor of pathologic complete response to neoadjuvant chemotherapy in patients with HER2-positive (HER2+) noninflammatory breast cancer (non-IBC) regardless of the results on HER2 immunohistochemical testing. In the future, some patients with HER2+ non-IBC and a high HER2 FISH ratio might even be offered personalized treatment options, such as nonsurgical treatment.

The efficacy of first-line chemotherapy in endocrine-resistant hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer.

PURPOSE: Combinations of endocrine therapy (ET) and targeted therapy (CDK4/6 or mTOR inhibitors) are standard of care for HR+/HER2- metastatic breast cancer (MBC). When ET is not effective, chemotherapy is commonly used. However, clinical outcomes of chemotherapy in the endocrine-resistant setting are limited. The purpose of this study was to identify predictive factors and the compare efficacies of chemotherapy agents in endocrine-resistant MBC. METHODS: We conducted a retrospective study of patients with HR+/HER2- MBC who received chemotherapy after progression on ET with or without targeted therapy at MD Anderson Cancer Center from 1999 to 2017. We collected baseline clinicopathological and all treatment data. Primary endpoint was time to treatment failure (TTF) of first-line chemotherapy for MBC. RESULTS: For the 1258 patients analyzed, mean age was 55.3 years (range 21-91). Previous treatment with targeted therapy was recorded for 390 patients (31%): 264 with CDK4/6 inhibitor, 205 with mTOR inhibitor, and 79 treated with both. The most frequent chemotherapy agents were capecitabine (48.9%) and taxanes (28.6%). After adjustment for all factors in a multivariate model, previous treatment with a CDK4/6 inhibitor had the strongest negative effect on TTF regardless of ET duration (hazard ratio [HR] 1.84; 95%CI 1.49-2.27; p < 0.001). Conversely, capecitabine had significantly longer median TTF than taxanes regardless of whether patients had prior exposure to taxanes in primary setting (6.1 vs 4.9 months; HR 0.64; 95%CI 0.55-0.75; p < 0.001). CONCLUSIONS: Previous exposure to CDK4/6 inhibitor had a negative predictive effect for the efficacy of chemotherapy. Capecitabine had the best efficacy against endocrine-resistant breast cancer.

Energy Constrained Optimization for Spreading Factor Allocation in LoRaWAN.

This paper discusses a spreading factor allocation for Long Range Wide Area Network (LoRaWAN). Because Long Range (LoRa) is based on chirp spread spectrum that each spreading factor is approximately orthogonal to each other, the performance of LoRaWAN can be enhanced by allocating the spreading factor appropriately to end devices (EDs). Several spreading factor allocation techniques have been reported. Techniques shown in existing studies can improve some characteristics (e.g. throughput or packet reception probability (PRP)); however, there are a few studies that have focused on the energy consumption of the EDs. The LoRa communication offers a low power communication and this enables the improvement of the performance in exchange for the energy consumption. This paper presents a performance improvement technique via spreading factor allocations for LoRaWAN. We define the optimization problem for the spreading factor allocation to maximize the PRP under a constraint for the average energy consumption of all the EDs. It enables for the performance improvement under the constraint of the average energy consumption of all the EDs by solving the problem. This study further develops a method to solve the defined problem based on a distributed genetic algorithm, which is metaheuristics method. Although the techniques shown in the existing studies give the average energy consumption as a result of the performance improvement by the spreading factor allocation, the presented technique can enhance the LoRaWAN performance by allocating the spreading factor to EDs under the constraint for the average energy consumption of all the EDs. Numerical examples validate the effectiveness of the presented technique. The PRP performance of the presented technique is superior to that of the techniques shown in the existing studies despite that the average energy consumption of all the EDs of the presented technique is less than that of the techniques shown in the existing studies.

Prediction of Bone Metastasis in Inflammatory Breast Cancer Using a Markov Chain Model.

BACKGROUND: Inflammatory breast cancer (IBC) is a rare yet aggressive variant of breast cancer with a high recurrence rate. We hypothesized that patterns of metastasis differ between IBC and non-IBC. We focused on the patterns of bone metastasis throughout disease progression to determine statistical differences that can lead to clinically relevant outcomes. Our primary outcome of this study is to quantify and describe this difference with a view to applying the findings to clinically relevant outcomes for patients. SUBJECTS, MATERIALS, AND METHODS: We retrospectively collected data of patients with nonmetastatic IBC (n = 299) and non-IBC (n = 3,436). Probabilities of future site-specific metastases were calculated. Spread patterns were visualized to quantify the most probable metastatic pathways of progression and to categorize spread pattern based on their propensity to subsequent dissemination of cancer. RESULTS: In patients with IBC, the probabilities of developing bone metastasis after chest wall, lung, or liver metastasis as the first site of progression were high: 28%, 21%, and 21%, respectively. For patients with non-IBC, the probability of developing bone metastasis was fairly consistent regardless of initial metastasis site. CONCLUSION: Metastatic patterns of spread differ between patients with IBC and non-IBC. Selection of patients with IBC with known liver, chest wall, and/or lung metastasis would create a population in whom to investigate effective methods for preventing future bone metastasis. IMPLICATIONS FOR PRACTICE: This study demonstrated that the patterns of metastasis leading to and following bone metastasis differ significantly between patients with inflammatory breast cancer (IBC) and those with non-IBC. Patients with IBC had a progression pattern that tended toward the development of bone metastasis if they had previously developed metastases in the liver, chest wall, and lung, rather than in other sites. Selection of patients with IBC with known liver, chest wall, and/or lung metastasis would create a population in whom to investigate effective methods for preventing future bone metastasis.

ID Insertion and Data Tracking with Frequency Offset for Physical Wireless Parameter Conversion Sensor Networks.

As the applications of the internet of things are becoming widely diversified, wireless sensor networks require real-time data reception, accommodation of access from several sensors, and low power consumption. In physical wireless parameter conversion sensor networks (PhyC-SN), all the sensors use frequency shift keying as the modulation scheme and then access the channel to the fusion center, simultaneously. As a result, the fusion center can recognize the statistical tendency of all the sensing results at a time from the frequency spectrum of the received signal. However, the information source, i.e., the sensor, cannot be specified from the received signal because no ID-indicating sensor is inserted to the signal. The data-tracking technique for tracing the time continuity of the sensing results is available for decomposing the sequence of the sensing results per sensor but the error tracking, which is a wrong recognition between the sensing results and the sensor, occurs owing to the similarity of the sensing results. This paper proposes the sensing result separation technique using a fractional carrier frequency offset (CFO) for PhyC-SN. In the proposed scheme, the particular fractional CFO is assigned to each user and it is useful for the ID specifying sensor. The fractional CFO causes inter-carrier interference (ICI). The ICI cancellation of the narrowband wireless communications is proposed. The two types of data-tracking techniques are proposed and are selectively used by the fusion center. Since the proposed data-tracking technique is multi-dimensional, high accuracy of data tracking is achieved even under the similar tendency of the sensing results. Based on computer simulation, we elucidate the advantage of the proposed sensing results separation.

Impact of change in body mass index during neoadjuvant chemotherapy and survival among breast cancer subtypes.

PURPOSE: We hypothesized that an increase in BMI category during neoadjuvant chemotherapy (NAC) would be associated with pathological complete response (pCR) rate and worse survival outcomes in primary breast cancer patients. METHODS: We reviewed the records of 4029 patients with stage I-III breast cancer who had undergone NAC and definitive surgery at our institution between May 1, 1990 and April 30, 2013. BMI values at baseline and after NAC were recorded, and the corresponding BMI category was assessed with the WHO classification. Overall survival (OS) and recurrence-free survival (RFS) were estimated using the Kaplan-Meier method, and multivariate Cox regression models were used to estimate the effect of covariates of interest on OS and RFS. RESULTS: The median follow-up period was 3.95 years. A change in BMI category from normal to obese during NAC was independently associated with shorter OS duration than was maintaining a normal weight [hazard ratio (HR) 1.637; 95%CI 1.066-2.514; p = 0.0242]. Kaplan-Meier curves among breast cancer subtypes showed differences, and a decrease in BMI led to better RFS and OS rates in obese patients with HR+/HER2- disease; those who maintained BMI also showed better prognosis for triple-negative breast cancer (TNBC). We saw no association between BMI change and pCR rate. CONCLUSION: Our data suggest that inability to maintain normal weight during NAC is a predictive marker of poor survival but not pCR. It may be important for patients to maintain a normal weight during NAC.

Radiomics to predict immunotherapy-induced pneumonitis: proof of concept.

We present the first reported work that explores the potential of radiomics to predict patients who are at risk for developing immunotherapy-induced pneumonitis. Despite promising results with immunotherapies, immune-related adverse events (irAEs) are challenging. Although less common, pneumonitis is a potentially fatal irAE. Thus, early detection is critical for improving treatment outcomes; an urgent need to identify biomarkers that predict patients at risk for pneumonitis exists. Radiomics, an emerging field, is the automated extraction of high fidelity, high-dimensional imaging features from standard medical images and allows for comprehensive visualization and characterization of the tissue of interest and corresponding microenvironment. In this pilot study, we sought to determine whether radiomics has the potential to predict development of pneumonitis. We performed radiomic analyses using baseline chest computed tomography images of patients who did (N = 2) and did not (N = 30) develop immunotherapy-induced pneumonitis. We extracted 1860 radiomic features in each patient. Maximum relevance and minimum redundancy feature selection method, anomaly detection algorithm, and leave-one-out cross-validation identified radiomic features that were significantly different and predicted subsequent immunotherapy-induced pneumonitis (accuracy, 100% [p = 0.0033]). This study suggests that radiomic features can classify and predict those patients at baseline who will subsequently develop immunotherapy-induced pneumonitis, further enabling risk-stratification that will ultimately lead to better treatment outcomes.

Incidence of immune-related adverse events and its association with treatment outcomes: the MD Anderson Cancer Center experience.

Background Immunotherapy is emerging as the cornerstone for treatment of patients with advanced cancer, but significant toxicity (immune-related adverse events [irAEs]) associated with unbridled T cell activity remains a concern. Patients and methods A retrospective review of the electronic medical records of 290 patients with advanced cancer treated on an immunotherapy-based clinical trial in the Department of Investigational Cancer Therapeutics at The University of Texas MD Anderson Cancer Center between February 2010 and September 2015 was performed. Clinical and laboratory parameters were collected to determine the incidence of irAEs, risk factors, and their association with treatment outcomes. Results Ninety eight of 290 patients (34%) experienced any grade irAEs. Among the 15 (5.2%) patients with grade ≥ 3 irAEs, the most common irAEs were dermatitis and enterocolitis. Although 80% of the patients with grade ≥ 3 irAEs required systemic corticosteroids, all the 15 patients recovered from the irAEs. On re-challenge, 4 of the 5 patients who had received systemic corticosteroids for irAE continued to respond. There were no irAE-related deaths. Importantly, patients with grade ≥ 3 irAEs had improved overall response rate (25 vs. 6%; p = 0.039) and longer median time to progression (30 weeks vs. 10 weeks; p = 0.0040) when compared to those without grade ≥ 3 irAEs. Conclusion Incidence of irAEs with immunotherapeutic agents indicates an active immune status, suggestive of potential clinical benefit to the patient. Further validation of this association in a large prospective study is warranted.

Crowdsourcing-Assisted Radio Environment Database for V2V Communication.

In order to realize reliable Vehicle-to-Vehicle (V2V) communication systems for autonomous driving, the recognition of radio propagation becomes an important technology. However, in the current wireless distributed network systems, it is difficult to accurately estimate the radio propagation characteristics because of the locality of the radio propagation caused by surrounding buildings and geographical features. In this paper, we propose a measurement-based radio environment database for improving the accuracy of the radio environment estimation in the V2V communication systems. The database first gathers measurement datasets of the received signal strength indicator (RSSI) related to the transmission/reception locations from V2V systems. By using the datasets, the average received power maps linked with transmitter and receiver locations are generated. We have performed measurement campaigns of V2V communications in the real environment to observe RSSI for the database construction. Our results show that the proposed method has higher accuracy of the radio propagation estimation than the conventional path loss model-based estimation.

Nomogram to predict pathologic complete response in HER2-positive breast cancer treated with neoadjuvant systemic therapy.

BACKGROUND: Pathologic complete response (pCR) is associated with improved survival outcomes in patients with HER2-positive primary breast cancer. We developed a nomogram to predict the probability of pCR rates by using oestrogen receptor (ER) expression, progesterone receptor (PR) expression and HER2/CEP17 ratio as continuous variables. METHODS: We retrospectively reviewed patients with stages I-III HER2-positive invasive breast cancer who had definitive surgery in 1999-2015 and received neoadjuvant systemic therapy (NST). Multivariate logistic regression models were applied to assess the effect of variables on pCR. A nomogram was built to estimate the probability of pCR. The discriminative ability was estimated by the concordance index (C-index). The accuracy was assessed graphically with a calibration curve. RESULTS: A total of 793 patients were included in the analysis. Low ER expression (P<0.001), high HER2/CEP12 ratio (P=0.03), and non-inflammatory breast cancer subtype (P=0.003) were associated with increased pCR rates. Regimens containing trastuzumab or trastuzumab and pertuzumab were associated with higher pCR rates than cytotoxic agents alone (P<0.001 and P<0.001, respectively). The C-index was 0.69. The calibration curve showed good agreement. CONCLUSIONS: Our nomogram predicted the pCR rate after NST among patients with HER2-positive primary breast cancer using clinicopathologic factors.

Poor prognosis of patients with triple-negative breast cancer can be stratified by RANK and RANKL dual expression.

PURPOSE: As clinical studies have correlated RANK expression levels with survival in breast cancer, and that RANK signaling is dependent on its cognate ligand RANKL, we hypothesized that dual protein expression further stratifies the poor outcome in TNBC. METHODS: RANK mRNA and protein expression was evaluated in TNBC using genomic databases, cell lines and in a tissue microarray of curated primary tumor samples derived from 87 patients with TNBC. RANK expression was evaluated either by Mann-Whitney U test on log-normalized gene expression data or by Student's t test on FACS data. Analysis of RANK and RANKL immunostaining was calculated by H-score, and correlations to clinical factors performed using χ 2 or Fisher's exact test. Associations with RFS and OS were assessed using univariate and multivariate Cox proportional hazard models. Survival estimates were generated using the Kaplan-Meier method. RESULTS: In three distinct datasets spanning 684 samples, RANK mRNA expression was higher in primary tumors derived from TNBC patients than from those with other molecular subtypes (P < 0.01). Cell surface-localized RANK protein was consistently higher in TNBC cell lines (P = 0.037). In clinical samples, TNBC patients that expressed both RANK and RANKL proteins had significantly worse RFS (P = 0.0032) and OS (P = 0.004) than patients with RANK-positive, RANKL-negative tumors. RANKL was an independent, poor prognostic factor for RFS (P = 0.04) and OS (P = 0.01) in multivariate analysis in samples that expressed both RANK and RANKL. CONCLUSIONS: RANK and RANKL co-expression is associated with poor RFS and OS in patients with TNBC.

High HER2/Centromeric Probe for Chromosome 17 Fluorescence In Situ Hybridization Ratio Predicts Pathologic Complete Response and Survival Outcome in Patients Receiving Neoadjuvant Systemic Therapy With Trastuzumab for HER2-Overexpressing Locally Advanced Breast Cancer.

BACKGROUND: The present study was performed to determine whether the human epidermal growth factor receptor-related 2 (HER2)/centromeric probe for chromosome 17 fluorescence in situ hybridization (FISH) ratio is a predictor of a pathologic complete response (pCR), recurrence-free survival (RFS), and/or overall survival (OS) in patients receiving neoadjuvant systemic treatment (NST) with trastuzumab (NST-T) for HER2+ locally advanced breast cancer (LABC). PATIENTS AND METHODS: The present retrospective study included 555 patients with HER2+ LABC who had undergone NST and definitive surgery (1999-2012); 373 had concurrently received trastuzumab. HER2-positivity was considered present with an immunohistochemical score of 3+ and/or HER2 FISH ratio of ≥2.0. We used logistic regression analysis and Cox proportional hazard modeling to determine whether a high HER2 FISH ratio, either as a continuous variable or with a cutoff of ≥7.0, would predict for pCR (no invasive disease in the breast and no tumor in the ipsilateral axillary lymph nodes), RFS, and/or OS. RESULTS: The pCR group's median HER2 FISH ratio was significantly higher than that of the non-pCR group (6.4 vs. 5.2; p = .003). The logistic regression model demonstrated that the independent predictors of pCR included a high HER2 FISH ratio as a continuous variable (p = .04). The multicovariate Cox proportional hazard model showed that a high HER2 FISH ratio (with a cutoff of ≥7.0 or as a continuous variable) was a significant prognostic indicator of longer RFS time (p = .047 and p = .04, respectively). Similarly, a high HER2 FISH ratio of ≥7.0 was associated with longer OS (p = .06). CONCLUSION: A high HER2 FISH ratio is a predictor of pCR in patients with HER2+ LABC who receive NST-T. IMPLICATIONS FOR PRACTICE: This study demonstrated the optimal predictive and prognostic value of a HER2/centromeric probe for chromosome 17 FISH ratio for primary HER2+ breast cancer treated with trastuzumab combined with neoadjuvant systemic treatment (NST-T). This suggests that a high HER2 FISH ratio is a potential indicator for a high pathologic complete response rate and a better prognosis when patients are treated with NST-T.

Impact of clinical trial on survival outcomes.

The number of patients with breast cancer who participate in therapeutic clinical trials remains low. One reason is a lack of opportunity; another is health care providers who do not recommend trials because they fear poorer outcome from the use of new drugs. Thus, we compared survival outcome in patients with metastatic breast cancer (MBC) who participated in first-line therapeutic clinical trials with outcome in patients who had never enrolled in a clinical trial and received only standard care. We hypothesized that first-line therapeutic clinical trials does not have a negative survival outcome. We reviewed the records of patients with MBC who were treated at MD Anderson Cancer Center between January 2000, and December 2010. The medical records of 5501 patients with MBC were screened, and 652 patients-285 in the trial arm and 367 in the control arm-met our specific eligible criteria. The median follow-up of our cohort was 7.16 years (95 % confidence interval [CI] 6.53-7.64 years). Among the global population, no significant differences in progression-free survival (PFS) or overall survival (OS) were observed between the treatment arms: for the clinical trial cohort, median PFS was 7 months (95 % CI 5.72-8.71 months), and median OS was 28.48 months (95 % CI 22.70-34.60 months). For the control cohort, median PFS was 10.02 months (95 % CI 7.13-11.99 months), and median OS was 28.71 months (95 % CI 24.41-31.31 months) (P = .089 and .335, respectively). Enrollment in first-line MBC therapeutic clinical trials does not result in less favorable survival outcome than that in MBC patients who never enrolled in a clinical trial.

Impact of androgen receptor expression in fluoxymesterone-treated estrogen receptor-positive metastatic breast cancer refractory to contemporary hormonal therapy.

PURPOSE: The purpose of this study is to evaluate survival outcome in patients with hormone receptor (HR)-positive (+) metastatic breast cancer (MBC) who received fluoxymesterone after disease progression while receiving contemporary hormonal therapy, as well as the association between estrogen receptor (ER)/androgen receptor (AR) status and survival outcome in these patients. METHODS: We retrospectively identified 103 patients treated with fluoxymesterone for HR + MBC from 2000 to 2014 and with at least one previous hormonal therapy in a metastatic setting. RESULTS: A median of 3 (range 1-10) hormonal therapies (aromatase inhibitors, tamoxifen, and/or fulvestrant) were received before fluoxymesterone; 33 patients discontinued fluoxymesterone before progression because of physician decision or adverse events including toxicity in 14 patients. Of the remaining 70 patients, 2 (3 %) had complete response, 7 (10 %) partial response, and 21 (30 %) stable disease for at least 6 months, yielding a clinical benefit rate of 43 %. The median PFS was 3.9 months (95 % CI 3.2-5.3 months). Multivariate analysis revealed no significant association between PFS and the type or number of prior systemic treatments. All 39 patients who had archived tumor slides available for AR staining had ER + carcinoma; 10 had ≥1 % but <10 %, 18 had ≥10 %, and 11 had no AR nuclear expression. AR positivity with various cutoffs (i.e. any AR + cells, ≥1 % AR + cells, or ≥10 % AR + cells) was not significantly associated with survival outcome. CONCLUSIONS: Fluoxymesterone can be considered for patients whose ER + MBC progresses on contemporary hormonal therapy, regardless of the level of AR expression.