Breast-Conserving Surgery
This technique aims to minimize the cosmetic impact and improve the patient's quality of life compared to a mastecomy.
The procedure involves removing the tumor along with a small margin of healthy tissue surrounding it, rather than the entire breast.
Breast-Conserving Surgery is often followed by radiation therapy to ensure complete removal of any remaining cancer cells.
This approach has become the preffered treatment option for many early-stage breast cancer patients, offering effective cancer management with improved aesthetic outcomes.
Most cited protocols related to «Breast-Conserving Surgery»
% Censored | KM | 84 | 86 | 76 | 78 | 86 |
CR | 58 | 67 | 44 | 57 | 55 | |
10 year | KM | 6.3 | 5 | 15 | 11 | 5 |
CR | 5.9 | 4 | 11 | 7 | 5 | |
20 year | KM | 22.6 | 20 | 42 | 32 | 19 |
CR | 17.8 | 15 | 27 | 21 | 14 | |
30 year | KM | 39.0 | 45 | 53 | 45 | 34 |
CR | 27.8 | 31 | 32 | 31 | 23 | |
40 year | KM | 47.8 | 52 | 68 | 45 | 44 |
CR | 31.8 | 34 | 35 | 31 | 27 |
Column 3 (‘Overall’) shows the cumulative incidence for all the 755 patients. Columns 4, 5, 6 and 7 show the cumulative incidence estimates for patients in complementation groups A, C, G and O (mostly nontyped patients and a small number of patients in uncommon complementation groups). The sample size is denoted N. The number of haematologic malignancy events is denoted by HEM and is given in parentheses in the second row.
% Censored | KM | 86 | 71 | 87 |
CR | 77 | 64 | 79 | |
1 year | KM | 0.3 | 3.6 | 0.0 |
CR | 0.3 | 3.6 | 0.0 | |
5 year | KM | 4.4 | 10.9 | 3.7 |
CR | 4.3 | 10.7 | 3.7 | |
10 year | KM | 14.2 | 28.4 | 12.8 |
CR | 13.6 | 27.0 | 12.3 | |
15 year | KM | 18.6 | 37.3 | 16.7 |
CR | 17.6 | 35.2 | 15.9 |
Column 3 (‘Overall’) shows the cumulative incidence for all the 305 breast cancer patients. Columns 4 and 5 show the cumulative incidence estimates for patients with and without a BRCA mutation. The sample size is denoted N. The number of breast cancer-specific deaths is denoted BCSS and is given in parentheses in the second row. One patient without a BRCA mutation had missing death status and hence was excluded from the analysis.
The cumulative incidences in the various groups can be compared using nonparametric tests, namely the log-rank test (Kalbfleisch and Prentice 1980 ) when calculating incidences based on the Kaplan–Meier approach or a modified χ2 test (Gray, 1988 ) when calculating incidences in the presence of competing risks. The cumulative incidence estimation methods outlined above are nonparametric, that is, these estimates are not based upon any specific model. Alternative model-based approaches can also be utilized to estimate cumulative incidences of specific events, adjusting for prognostic factors of interest. Under the assumption of noninformative censoring, the Cox proportional hazards model (Cox, 1972 ) can be used. In the presence of competing risk events, a modified Cox proportional hazards model or the competing risk regression approach has been developed by Fine and Gray (1999) . We do not detail these methods here, but refer the reader to the references provided above.
Most recents protocols related to «Breast-Conserving Surgery»
A Cox proportional hazards model was constructed to estimate the independent effects of the three GA domains on the survival rate during a 6-year follow-up period, after adjustment for age, tumour stage, lymph node (LN) stage, and intrinsic molecular subtype. The primary outcome was OS time, which was defined as the time from the date of cancer diagnosis to the date of death from any cause or the date on which the patient was last known to be alive. The estimated effects of the three GA domains on OS were calculated as hazard ratios (HRs) and 95% confidence intervals (CIs). Adjusted survival curves stratified by the categories of the three GA domains were also generated. To examine the effects of the three GA domains on OS and BCSS, we constructed a Cox proportional hazards model after adjusting for age, tumour stage, LN stage, and intrinsic molecular subtype.
To assess the incremental prognostic value of each GA domain, we estimated Harrell’s concordance statistic (C‐statistic) for different models for OS and BCSS. The C‐statistic is equivalent to the area under the receiver operating characteristic curve, with a value of 0.5 indicating random predictions and a value of 1.0 indicating perfect discrimination between survivors and non-survivors. The first model was a ‘basic’ model that controlled for age, tumour stage, LN stage, and intrinsic molecular subtype. The GA domains were then individually added to the basic model. The final model was a ‘full’ model that included all three GA domains in addition to the covariates in the basic model.
All analyses were conducted using R software version 4.1.3. A two-sided P-value of <0.05 was considered statistically significant.
In our study, a DL network generated sCT images from CBCT images. And then, pCT was aligned with CBCT and sCT images, respectively, using the DIR method. Next, the contours on pCT were propagated on CBCT (sCT) images. Physicians first manually outlined pCT and CBCT data contours (target area contours including tumor bed area clinical target volume (CTV) 1, CTV 2, Heart). The final contours propagated on the sCT images have a more similar anatomy to the original CBCT, especially in soft tissues with significant effects. The model was trained, validated, and tested using 52/7/41 patients, corresponding to 4160/560/3280 slices.
Brucella canis rough antigen that was used in the RSAT and 2-ME TAT was prepared from heat-killed cells of B. canis reference strain RM666 suspended in a formalized phosphate-buffered saline solution. Brucella canis 2-ME TAT antigen was obtained from the National Veterinary Services Laboratory (NVSL) Ames IA 50010, USA. Both RSAT and 2-ME TAT were carried out in this study to detect antibodies against B. canis, according to the technique adopted by Alton et al. [1 ].
RBT and BAPAT originating from smooth Brucellaabortus antigens were performed in this study to test dog blood samples for the detection of smooth Brucella antibodies according to the techniques described by Alton et al. [1 ] and World Organization for Animal Health (WOAH) [2 ].
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More about "Breast-Conserving Surgery"
This technique aims to minimize the cosmetic impact and improve the patient's quality of life compared to a mastectomy.
The procedure involves removing the tumor along with a small margin of healthy tissue surrounding it, rather than the entire breast.
Breast-Conserving Surgery is often followed by radiation therapy to ensure complete removal of any remaining cancer cells.
This approach has become the preferred treatment option for many early-stage breast cancer patients, offering effective cancer management with improved aesthetic outcomes.
Researchers and clinicians often utilize statistical software, such as SPSS (Statistical Package for the Social Sciences) version 20 or 22.0, R version 3.6.1, SAS 9.4, or STATA version 12, to analyze data and evaluate the outcomes of Breast-Conserving Surgery.
Additionally, treatment planning systems like the Eclipse system may be used to plan and deliver radiation therapy after the surgery.
The reproducibility and accuracy of Breast-Conserving Surgery research protocols are crucial for advancing this treatment approach.
PubCompare.ai's AI-driven platform can enhance these aspects by helping researchers effortlessly locate and compare protocols from literature, pre-prints, and patents to identify the best options for their research needs.
By leveraging the power of AI-driven analysis, researchers can optimize their Breast-Conserving Surgery research and contribute to the ongoing improvement of this important cancer treatment.