Materiały źródłowe

• #1 Prognosis and survival for breast cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/breast/prognosis-and-survival

  A prognosis is the doctors best estimate of how cancer will affect you and how it will respond to treatment. Survival is the percentage of people with a disease who are alive at some point in time after their diagnosis. Prognosis and survival depend on many factors. […] The stage is the main prognostic factor for breast cancer. It describes how much cancer is in the body, where it is and how far it has spread. Early-stage breast cancer is less likely to come back (recur), so it has a more favourable prognosis. Breast cancer that is diagnosed at a later stage has a greater risk of recurrence, so it has a less favourable prognosis. […] Breast cancer that has spread to lymph nodes has a higher risk of coming back and a less favourable prognosis than breast cancer that has not spread to any lymph nodes.

• #2 Breast Cancer Facts & Stats 2024 – Incidence, Age, Survival, & More

  https://www.nationalbreastcancer.org/breast-cancer-facts/

  1 in 8 women in the United States will be diagnosed with breast cancer in her lifetime. […] But there is hope. When caught in its earliest, localized stages, the 5-year relative survival rate is 99%. […] Generally speaking, the earlier the cancer is detected, the greater the likelihood of a successful outcome. […] Risk of breast cancer recurrence depends on the type and staging of the initial breast cancer. Typically, the highest risk of recurrence is during the first few years after treatment and decreases over time. […] The 5-year relative survival rate for cancer diagnosed at the localized stage is 99%. […] Breast cancer survival rates are calculated using different forms of data, including the type and staging of breast cancer at diagnosis. […] The 5-year relative survival rate in the U.S. for all types and stages of breast cancer combined is 91%.

• #3 Understanding Breast Cancer Survival Rates | Susan G. Komen®

  https://www.komen.org/breast-cancer/facts-statistics/breast-cancer-statistics/survival-rates/

  A 5-year breast cancer-specific survival rate shows the percentage of people who have not died from breast cancer 5 years after diagnosis. […] These rates vary by breast cancer stage. […] For example, the 5-year relative survival rate for localized breast cancer in the U.S. is 99%. This means women with localized breast cancer are, on average, 99% as likely to live 5 years beyond diagnosis as women in the general population. […] Relative survival rates compare survival rates for women with breast cancer to survival rates for women in the general population over the same period of time. […] Comparing mortality rates, we can see women who live in Washington D.C. have higher rates of breast cancer mortality (and thus, lower rates of breast cancer survival) than women in California.

• #4 Prognostic models for breast cancer: a systematic review | BMC Cancer | Full Text

  https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-5442-6

  Prognosis for breast cancer is important in several ways. Firstly, it informs patients about the future course of their illness. […] The more precise is the outcome predicted, the better a patient is allocated the right treatment. […] Many models have been developed to predict breast cancer prognosis. […] The most commonly used prognostic factors in the models were nodal status, tumour size, and tumour grade, followed by age at diagnosis and ER status. […] The NPI was one of the simplest and oldest models, and included only nodal status, tumour size, and tumour grade. […] The performance of a particular model may vary across different populations. […] Most studies in our review showed that models were less accurate in patients aged under 40 years or over 65 years, although some studies showed opposite results.

• #5 An overview of prognostic factors for long-term survivors of breast cancer

  https://pmc.ncbi.nlm.nih.gov/articles/PMC2217620/

  Numerous studies have examined prognostic factors for survival of breast cancer patients, but relatively few have dealt specifically with 10+-year survivors. […] 10-year breast cancer survivors showed 90% 5-year relative survival. Tumor size, nodal status and grade remained the most important prognostic factors for long-term survival, although their role decreased over time. […] The prognosis for breast cancer patients who have survived at least 10 years is favourable and increases over time. Improved long-term survival can be achieved by earlier detection, more effective modern therapy and healthier lifestyle. […] The longer a woman survives BC the more the prognosis improves, illustrated by conditional survival. […] Patients with recurrent, metastasized or second cancer generally exhibited lower long-term survival than those without.

• #6 Development of Predictive Models for Survival among Women with Breast Cancer in Malaysia

  https://www.mdpi.com/1660-4601/19/22/15335

  The stage at diagnosis remained the most important predictor of cancer survival. Other important clinical determinants are histological type and cancer grade. Biomarkers, such as the estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) became prominent prognostic factors, as new evidence emerged and more women were diagnosed early. Additionally, sociodemographic factors such as ethnicity, marital status and age at diagnosis were shown to alter breast cancer survival probability significantly. […] The estimated five-year survival for all data was 60.5% (95% CI: 57.6, 63.6). The five-year survival status and overall survival were not statistically significant between derivation and validation datasets, ensuring reliable validation findings.

• #7 Machine learning techniques for breast cancer diagnosis and treatment: a narrative review – Sugimoto – Annals of Breast Surgery

  https://abs.amegroups.org/article/view/7085/html

  The advent of new bioinformatic approaches and artificial intelligence-based computational technologies has led to a shift in the decision-making of oncologists regarding breast cancer diagnostics and treatment processes. […] Clinical-pathological features have been conducted by multivariable analysis to predict various outcomes, e.g., the sensitivity of adjuvant therapy and prognosis. […] ML-based prediction methods are powerful tools and contribute to realizing personalized medicine for breast cancer. […] The Nottingham prognostic index (NPI) was developed in 1982 and involved three factors, namely tumor size, stage of the disease, and tumor grade, to predict the prognosis of primary and operable breast cancers. […] Various other factors, such as the vascular endothelial growth factor (VEGF), are prognostic factors independent of the NPI for patients with node-negative breast cancers.

• #8 Survival for breast cancer | Cancer Research UK

  https://www.cancerresearchuk.org/about-cancer/breast-cancer/survival

  Breast cancer is the most common cancer in the UK. Survival for breast cancer is generally good, particularly if you are diagnosed early. This is probably because of screening, early diagnosis and improved treatment. […] Survival depends on many different factors. So no one can tell you exactly how long you will live. It depends on your: type and stage of cancer, level of fitness, previous treatment. […] Your doctor can give you more information about your own outlook (prognosis). […] Most women (almost 100%) will survive their cancer for 5 years or more after diagnosis. […] 90 out of 100 women (90%) will survive their cancer for 5 years or more after diagnosis. […] More than 70 out of 100 women (more than 70%) will survive their cancer for 5 years or more after diagnosis. […] More than 25 out of 100 women (more than 25%) will survive their cancer for 5 years or more after they are diagnosed. The cancer is not curable at this point, but may be controlled with treatment for some years.

• #9 Survival Rates for Breast Cancer | American Cancer Society

  https://www.cancer.org/cancer/types/breast-cancer/understanding-a-breast-cancer-diagnosis/breast-cancer-survival-rates.html

  Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. They cant tell you how long you will live, but they may help give you a better understanding of how likely it is that your treatment will be successful. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. These statistics can be confusing and may lead you to have more questions. Talk with your doctor, who is familiar with your situation, about how these numbers may apply to you. […] A relative survival rate compares women with the same type and stage of breast cancer to women in the overall population. For example, if the 5-year relative survival rate for a specific stage of breast cancer is 90%, it means that women who have that cancer are, on average, about 90% as likely as women who dont have that cancer to live for at least 5 years after being diagnosed.

• #10 Survival for breast cancer | Cancer Research UK

  https://www.cancerresearchuk.org/about-cancer/breast-cancer/survival

  Generally for women with breast cancer in England: Around 95 out of every 100 women (around 95%) survive their cancer for 1 year or more after diagnosis, Around 85 out of every 100 women (around 85%) will survive their cancer for 5 years or more after diagnosis, Around 75 out of every 100 women (around 75%) will survive their cancer for 10 years or more after diagnosis. […] Your outlook depends on the stage of the cancer when it was diagnosed. This means how big it is and whether it has spread. […] The type of cancer and grade of the cancer cells can also affect your survival. Grade means how abnormal the cells look under the microscope. […] Your general health and fitness also affect survival, the fitter you are, the better you may be able to cope with your cancer and treatment. […] Another factor that can affect survival is whether the cancer cells have receptors for particular cancer drugs. […] Statistics are averages based on large numbers of patients. They cant predict exactly what will happen to you. No two patients are exactly alike and response to treatment also varies from one person to another.

• #11 Breast Cancer Facts & Stats 2024 – Incidence, Age, Survival, & More

  https://www.nationalbreastcancer.org/breast-cancer-facts/

  The 5-year relative survival rate in the U.S. of localized (early stage) breast cancer is 99%. […] Breast cancer death rates have slowly decreased since 1989, for an overall decline of 43% through 2020. This is in part due to better screening and early detection efforts, increased awareness, and continually improving treatment options. […] Women who receive regular screenings for breast cancer have a 26% lower breast cancer death rate than women who do not receive screenings. […] Black men with breast cancer tend to have a worse prognosis, or outlook, than white men with breast cancer.

• #12

  https://link.springer.com/article/10.1007/s10549-016-3983-9

  Whether young age at diagnosis of breast cancer is an independent risk factor for death remains controversial, and the question whether young age should be considered in treatment decisions is still to be answered. […] At 10 years follow-up, women 35 years and 3539 years had a worse BCSS [age 35 years 69 % (HR 2.75, 95 % CI 1.933.94), age 3539 years 76 % (HR 2.33, 95 % CI 1.543.52), age 4049 years 84 % (HR 1.53, 95 % CI 0.972.39), and age 5069 years 89 % (reference)]. The worse BCSS was statistically significant in stages IIIa and Luminal B tumors. […] Young women have a high risk of systemic disease even when diagnosed in an early stage. The excess risk of relapse is most pronounced in Luminal B tumors, where low age is an independent prognostic factor of DDFS and LRFS. […] Young women with breast cancer have a worse prognosis than middle-aged women, partly explained by diagnosis at a later stage and by a higher proportion of unfavorable tumor characteristics.

• #13

  https://link.springer.com/article/10.1007/s10549-016-3983-9

  The increased risk of breast cancer death in young versus middle-aged women was significant during the earlier part of the studied period and mainly noted in tumors with favorable characteristics, namely: small tumor size, low grade, Her2-negativity, and no LVI. […] At 10-year follow-up, the BCSS was for women 35 years 69 % (HR 2.75, 95 % CI 1.933.94), for women 3539 years 76 % (HR 2.33, 95 % CI 1.543.52), for women 4049 years 84 % (HR 1.53, 95 % CI 0.972.39), and women 5069 years 89 % (HR = 1.00 reference). […] In the multivariate analysis, successively correcting for year of diagnosis, stage at diagnosis, detection mode, grade, subtype, and systemic treatment, young age (35 years and 3539 years) was an independent risk factor in LRFS (HR 2.13, 95 % CI 1.213.76 and HR 1.97, 95 % CI 1.063.68) but not in DDFS or BCSS. […] To conclude, the effect of age is modified by tumor subtype. Despite correction for biology and more intense treatment in the young, young age is an independent risk factor for systemic disease in women with early-stage luminal tumors, with a two-fold risk of distant disease.

• #14 Prognosis and survival for breast cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/breast/prognosis-and-survival

  The longer the period of time before breast cancer comes back, the better the prognosis. If breast cancer comes back more than 5 years after diagnosis, the outcome is usually better than when it recurs less than 2 years after diagnosis. […] Distant recurrence will be treated like chronic disease. This means that your healthcare team will offer treatments to slow the cancer’s spread and manage symptoms, rather than try to cure the cancer itself.

• #15 Predict Breast

  https://breast.predict.cam/

  Predict is an online tool that helps patients and clinicians see how different treatments for early invasive breast cancer might improve survival rates after surgery. […] It then uses data about the survival of similar women in the past to show the likely proportion of such women expected to survive up to fifteen years after their surgery with different treatment combinations. […] Patients should use it in consultation with a medical professional.

• #16 An updated PREDICT breast cancer prognostic model including the benefits and harms of radiotherapy | npj Breast Cancer

  https://www.nature.com/articles/s41523-024-00612-y

  PREDICT Breast (www.breast.predict.nhs.uk) is a prognostication tool for early invasive breast cancer. […] The aim of this study was to update PREDICT Breast to ensure that the underlying model is appropriate for contemporary patients. […] The new model was well-calibrated; predicted breast cancer deaths at 5-, 10- and 15-year were within 10 per cent of the observed validation data. […] The new PREDICT Breast model outperformed the current model and will be implemented in the online tool which should lead to more accurate absolute treatment benefit predictions for individual patients. […] The improvement in prognosis over time is reflected in the reclassification of breast cancer cases within the three categories of risk used by the Cambridge Breast Unit to guide the use of adjuvant chemotherapy.

• #17 An updated PREDICT breast cancer prognostic model including the benefits and harms of radiotherapy | npj Breast Cancer

  https://www.nature.com/articles/s41523-024-00612-y

  Overall, the model performed well in terms of discrimination and calibration in both model development data and the model validation data. […] In particular, we have included updated the model to reflect outcomes in contemporary patients and added the benefits of radiotherapy as well as the harms of both chemotherapy and radiotherapy. […] The new model has been validated in two independent population-based data sets from the United Kingdom and performs well.

• #18

  https://link.springer.com/article/10.1007/s10549-025-07654-1

  Outcome prediction research in early-onset breast cancer (EoBC) is limited. This study evaluated the predictive performance of NHS PREDICT v2.1 and developed two prediction models for 5-year and 10-year all-cause mortality in a cohort of EoBC patients in Alberta, Canada. […] PREDICT v2.1 tended to overestimate 5-year mortality in those with 30% predicted risks and 10-year mortality in those with 50% predicted risks for EoBC in Alberta, Canada. […] The calibration intercept showed that the average predicted probability was greater than the overall event proportion at 5 years, but not at 10 years. Overestimation of 5-year mortality was observed in ER-positive, HER2-positive, grade III, and T3 disease. […] While modern versions of PREDICT show better predictive performance in patients 40 years than previous versions, this tool does not reflect all locoregional and adjuvant treatment options specific to this age group. Decision-aid tools focused on the needs of younger breast cancer patients should become a research priority. The application of machine learning approaches did not improve outcome prediction compared with existing tools like PREDICT but predictors specific to EoBC should be investigated to support decision making in this setting.

• #19 Machine learning techniques for breast cancer diagnosis and treatment: a narrative review – Sugimoto – Annals of Breast Surgery

  https://abs.amegroups.org/article/view/7085/html

  The Nottingham prognostic index plus (NPI+) was developed using an ANN to combine a large number of molecular expression levels in a non-linear manner. […] The ability to visualize the relationships among the quantitative effects of each observed feature on the outcome would aid the decision-making process when selecting the treatment mode. […] A systematic review was published, evaluating a total of 58 mathematical prediction models for disease prognosis. […] Most of these models utilized Cox proportional hazards regression to predict mortality, recurrence, or both, and they were calibrated using the C-index or the area under the receiver operating curve (AUC). […] The pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) was predicted using various types of classification methods.

• #20 Prognostic models for breast cancer: a systematic review | BMC Cancer | Full Text

  https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-5442-6

  Breast cancer is the most common cancer in women worldwide, with a great diversity in outcomes among individual patients. The ability to accurately predict a breast cancer outcome is important to patients, physicians, researchers, and policy makers. Many models have been developed and tested in different settings. […] Overall, the models performed well in the development cohorts but less accurately in some independent populations, particularly in patients with high risk and young and elderly patients. An exception is the Nottingham Prognostic Index, which retains its predicting ability in most independent populations. […] Importantly, their performance was suboptimal in independent populations, particularly in patients with high risk and in young and elderly patients. […] In breast cancer patients, 5-year relapse-free survival (RFS) ranges from 65 to 80%, and 10-year overall survival (OS) ranges from 55 to 96%.

• #21 Survival Rates for Breast Cancer | American Cancer Society

  https://www.cancer.org/cancer/types/breast-cancer/understanding-a-breast-cancer-diagnosis/breast-cancer-survival-rates.html

  The SEER database tracks 5-year relative survival rates for breast cancer in the United States, based on how far the cancer has spread. […] These numbers are based on women diagnosed with breast cancer between 2014 and 2020. […] Women now being diagnosed with breast cancer may have a better outlook than these numbers show. Treatments improve over time, and these numbers are based on women who were diagnosed at least five years earlier. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment. […] These numbers dont take everything into account. Survival rates are grouped based on how far the cancer has spread, but your age, overall health, how well the cancer responds to treatment, tumor grade, the presence of hormone receptors on the cancer cells, HER2 status, and other factors can also affect your outlook. […] Survival rates for women with triple-negative breast cancer are different from those above. […] Survival rates for women with inflammatory breast cancer are different from those above.

• #22 Prognostic models for breast cancer: a systematic review | BMC Cancer | Full Text

  https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-5442-6

  We reviewed the development and/or validation of 58 models predicting mortality and/or recurrence for female breast cancer. These models varied in terms of methods of development and/or validation, predictors, outcomes, and patients included. Most models have been developed in Europe, Asia, and North America. We found that models performed well in internal validation cohorts, but the results were unpredictable in external validation cohorts, especially in young and elderly patients, and in high risk patients. NPI is an exception, which performed well in most independent populations. Therefore, models should be validated before being applied in another population.

• #23 Prognostic Tools for Older Women with Breast Cancer: A Systematic Review

  https://www.mdpi.com/1648-9144/59/9/1576

  Breast cancer is the most common cancer in women, and older patients comprise an increasing proportion of patients with this disease. […] A prognostic model taking into consideration unique factors, such as frailty and comorbidities, to predict the individual risk of recurrence, progression, and clinical outcomes for elderly women with breast cancer is critical to help guide treatment decisions in the clinical setting. […] We reviewed the development and validation of 17 models predicting response to treatment (including adjuvant radiation, chemotherapy, endocrine therapy, and surgery), frailty, and mortality specific to older patients with breast cancer. There is a wide variety of practices in the development and validation of these models, including the size of the studies, inclusion criteria, patient demographics, predictive factors included, and analytic strategies used. […] However, most of the models presented in this review represent promising tools for clinical application in the care of older patients with breast cancer.

• #24 Machine learning techniques for breast cancer diagnosis and treatment: a narrative review – Sugimoto – Annals of Breast Surgery

  https://abs.amegroups.org/article/view/7085/html

  ADTree-based prediction model also predicted the metastasis of the axillary lymph node in patients with breast cancer who had not received prior treatment. […] These models involve an ensemble technique, whereby multiple prediction models can be developed and their predictions can be integrated to enhance the prediction accuracies. […] The clinical utility of Oncotype DXTM was evaluated in large prospective trials. […] The improvement of automatic training and validation algorithm of each ML method is still necessary but enough validated ML models have shown the potential to contribute to the diagnosis and decision of treatment of breast cancers.

• #25 An overview of prognostic factors for long-term survivors of breast cancer

  https://pmc.ncbi.nlm.nih.gov/articles/PMC2217620/

  The prognosis decreases with larger primary tumour size, nodal involvement, higher grade, early recurrence (within 5 years of surgery), location of recurrence (regional rather than local ipsilateral) and inadequate primary cancer treatment. […] The influence of host factors including age, race/ethnicity or socio-economic factors and tumour-related factors such as histological type and angiogenesis diminishes after correction for other factors. […] Although a lot is known about the prognosis for BC patients, effect of traditional prognostic factors appears to attenuate over time, leaving room for studies on the role of other and newer factors for long-term survival.

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