Operable Breast NeoplasmsPREDICTNCT04985253
Correlation of Predictive Accuracy of PREDICT Version 2.2 of Indian Women With Operable Breast Cancer
An observational study of Operable Breast Neoplasms, run by Tata Memorial Centre at 1 site in India.
Trial summary
This is an observational retrospective study which aims at comparing the 5-year survival estimates from "PREDICT V2.2" with observed 5-year outcome from our dataset of Indian women treated for operable breast cancer. "PREDICT V2.2" is a prognostication and treatment benefit tool developed in the UK. Read more about this study
- Who is it for?
- Ages 18 to 99 years, women only
- Conditions the study is for
- Operable Breast Neoplasms
- What is being tested?
- prediction of overall survival using Web based PREDICTV2.0 portal
- How many people
- 2,780 participants
- Where
- 1 siteIndia
- Study dates
- 15 Nov 2018to 31 Dec 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 99 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Participant data will be selected from all the patients underwent treatment for Breast neoplasm in Tata Memorial Hospital Mumbai-12 in year 2010-2013.
Who may be able to join
- OBC patients treated at TMH
- ER +/Her2 neg or TNBC
- We will include2780 women wherein events / 5-year follow up is available. We propose to have a blinded member of the DMG identify such cases and provide to the study team.
Who cannot join
- . • Missing variables egpT size, chemotherapy details
- Lost to follow up
- Her2 overexpression positive or Equivocal on IHC. (This is being excluded to avoid the bias of incomplete treatment as a large number of patients treated in 2010-2013 may not have received Her2 targeted treatment in our setting)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Correlation of Predictive Accuracy of PREDICT Version 2.2, (PREDICT V2.2) on a Retrospective Cohort of Indian Women With Operable Breast Cancer (OBC)
This is an observational retrospective study which aims at comparing the 5-year survival estimates from "PREDICT V2.2" with observed 5-year outcome from our dataset of Indian women treated for operable breast cancer. "PREDICT V2.2" is a prognostication and treatment benefit tool developed in the UK. It is a tool available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions, for operable breast cancer patients. We hypothesize that 5-year overall survival (OS) predictions using "PREDICT V2.2" will have reasonable accuracy and applicability to the Indian operable breast cancer patients. The predictions, if accurate, will not only reassure the patients of the benefits of the treatment being offered, which outweigh the side effects but it will also make clinician as well as patient confident about avoiding potentially toxic systemic therapies, where the benefit is too small.
Read the detailed description
Adjuvant therapy for breast cancer is based on clinic-pathological prognostic and predictive markers.The most important prognostic marker is still presence of lymph node involvement1,2. Other factors that contribute to planning adjuvant systemic therapy include, tumor size3, grade3, hormone receptor status4, Her2/neu overexpression5-7, proliferation markers8-9, age at presentation, patient preferences, performance status and comorbidities. Accurate survival estimates, and the likely benefit of adjuvant therapy, are important aspects of information oncologists consider when making decisions following surgery for invasive, early breast cancer. Currently these decisions are based on known pathological prognostic factors including tumour size, tumour grade and lymph node status in addition to the relative risk reductions of any adjuvant therapy1-7.
The prognostic and predictive strengths of different factors are variable and the same factor can have different predictive or prognostic value according to the molecular subtype of breast cancer. These markers are not completely independent of each other10.
Several predictive models are now available to help estimate the survival and treatment benefits for individual patients.Multivariate Prediction Models (MPM) takes into consideration not just each marker but the effect with all possible combinations of these markers10. MPMs are of two types. They can either be multivariate prognostic model or a multigene predictive model. Examples10 of multivariate prognostic models are IHC4 assay, Adjuvant! Online and PREDICT. Multigene predictive models are OncotypeDx, MammaPrint, PAM50, EndoPredict.
Web based mathematical models which use algorithms to predict survival with or without systemic therapy after surgery, like 'Adjuvant! Online' and PREDICT V2.0 use patient characteristics to predict the survival with or without treatment. The inputs required are tumour size, number of nodes involved, grade of tumour, hormone receptor status, Her2 overexpression, Ki67 and comorbidities. Based on these inputs using an algorithm these tools calculate the overall survival at end of 5 and/or 10 years. Then they also predict what would be the added benefit of adjuvant systemic therapies singularly or with combinations.
However majority of these models that have been evaluated use the datasets of cancer registries in a particular geographical location or singles institute11,12. This makes blind application of these models to untested populations unpredictable. Various studies have tested web based prognostic models in different populations. In 2011 Hajage D, et al published their results regarding external validation of 'Adjuvant! Online',in a French and Dutch population13. The prediction was overall well-calibrated in the French data. But there was discordance in some subgroups of patients having high grade tumours and HER2 overexpression. Addition of HER2 status, Mitotic Index and Ki67 significantly improved the predictions. In the Dutch data set, the overall 10-year survival was overestimated by 'Adjuvant! Online', particularly in patients less than 40 years of age.Bhoopathyet al, in 2012 tested this tool in an Asian population and concluded that although it differentiates between good and bad prognosis, it systematically overestimates the survival and requires adaptation before usage in Asian population14.
Predict is an online prognostication and treatment benefit tool developed in the UK, using cancer registration and survival data recorded by the Eastern Cancer Registration and Information Centre (ECRIC) for 5694 women diagnosed in East Anglia from 1999-2003.15The model was validated in a second cohort of 5468 women from the West Midlands Cancer Intelligence Unit and is available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions. Wong et al, tested the predictive accuracy of PREDICT V1.0 in the southeast Asian population16. There were 67% Chinese patients while 13% were Indians. The median age in their study was 50 yrs. They showed concordance in observed and predicted OS in most subgroups except for women whore less than 40 years of age. After reviews in literature, for a better fit in various groups, PREDICT V1.0 was updated to version v2.0. V2.0 is equivalent to V1.0 but calibration of V2.0 has improved over V1.0 in patients diagnosed under the age of 40.17
Multigene predictive models like OncotypeDx, MammaPrint, PAM50, EndoPredict are restrictive in their use due to high cost, thus many oncologists in India use the freely available Web based mathematical models, like Adjuvant Online! or PREDICT V2.0. However, there is no data suggesting the validity of prediction using these models in Indian patients. Hence we propose a study to validate the tool within a trial setting, before advising its use in clinical practice.
With the aim to compare the 5-year survival estimates from Predict with observed 5-year outcome from the TMC dataset of Indian women treated for operable breast cancer.
- Conditions
- Operable Breast Neoplasms
- Being tested
- prediction of overall survival using Web based PREDICTV2.0 portal
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
prediction of overall survival using Web based PREDICTV2.0 portalOther
Predict is an online prognostication and treatment benefit tool developed in the UK, using cancer registration and survival data recorded by the Eastern Cancer Registration and Information Centre (ECRIC) for 5694 women diagnosed in East Anglia from 1999-2003.
The model was validated in a second cohort of 5468 women from the West Midlands Cancer Intelligence Unit and is available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions. Wong et al, tested the predictive accuracy of PREDICT V1.0 in the southeast Asian population. There were 67% Chinese patients while 13% were Indians. They showed concordance in observed and predicted OS in most subgroups except for women whore less than 40 years of age.
| Study group | Role | What they receive |
|---|---|---|
| Operable breast neoplasm cohort | Operable breast cancer (OBC) ER +/Her2 neg or triple negative breast cancer patients diagnosed and treated at Tata Memorial Centre, Mumbai from 01 Jan 2010 to 31 Dec 2013 with a five-year follow up or events within the 5 years. Receives: Other: prediction of overall survival using Web based PREDICTV2.0 portal |
What is being measured
The primary outcome is the main question the study is designed to answer.
Five year overall survival
To compare the observed 5 year overall survival of operable breast cancer patients with
the one predicted by PREDICT V 2.2
Measured: 5 years
Secondary outcomes (1)
To compare the observed 5 year overall survival of operable breast cancer patients with the one predicted by PREDICT V2.0V 2.2 for subgroups like age at diagnosis, stage of disease, tumour grade and molecular class (ER/PR positive or TNBC)
To compare the overall survival of 5 years, of breast cancer patients considering age, stage of disease, tumour grade and molecular class of disease with value predicted by PREDICT version 2.2
Measured: 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Aug 2021
- Study start15 Nov 2018
- Primary completion18 Oct 2021
- Study completion31 Dec 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (17)Papers the sponsor has linked to this study.
- Other trials for Operable Breast NeoplasmsStudies of the same condition, open and under way.
- More trials run by Tata Memorial CentreThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 2,780 participants (actual)
Sponsor and investigators
- Lead sponsor
- Tata Memorial Centre
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Nita Sukumar Nair, Tata Memorial Centre
- Investigators
- Nita S Nair, MCH, Principal investigator, Professor and Surgeon (Breast Oncology)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04985253
- Sponsor's protocol ID
- 3055
- Acronym
- PREDICT
- Status last verified
- Oct 2022
- First submitted
- 26 May 2020
- Last updated
- 20 Oct 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: To maintain the study participants data confidentiality and anonymity As per local regulations and Ethics committee mandate IPD will not be shared.
Publications
Saez RA, McGuire WL, Clark GM. Prognostic factors in breast cancer. Semin Surg Oncol. 1989;5(2):102-10. doi: 10.1002/ssu.2980050206.
PubMed 2657970Fisher B, Bauer M, Wickerham DL, Redmond CK, Fisher ER, Cruz AB, Foster R, Gardner B, Lerner H, Margolese R, et al. Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update. Cancer. 1983 Nov 1;52(9):1551-7. doi: 10.1002/1097-0142(19831101)52:93.0.co;2-3.
PubMed 6352003Koscielny S, Tubiana M, Le MG, Valleron AJ, Mouriesse H, Contesso G, Sarrazin D. Breast cancer: relationship between the size of the primary tumour and the probability of metastatic dissemination. Br J Cancer. 1984 Jun;49(6):709-15. doi: 10.1038/bjc.1984.112.
PubMed 6733019Hilsenbeck SG, Ravdin PM, de Moor CA, Chamness GC, Osborne CK, Clark GM. Time-dependence of hazard ratios for prognostic factors in primary breast cancer. Breast Cancer Res Treat. 1998;52(1-3):227-37. doi: 10.1023/a:1006133418245.
PubMed 10066085Borg A, Tandon AK, Sigurdsson H, Clark GM, Ferno M, Fuqua SA, Killander D, McGuire WL. HER-2/neu amplification predicts poor survival in node-positive breast cancer. Cancer Res. 1990 Jul 15;50(14):4332-7.
PubMed 1973070Winstanley J, Cooke T, Murray GD, Platt-Higgins A, George WD, Holt S, Myskov M, Spedding A, Barraclough BR, Rudland PS. The long term prognostic significance of c-erbB-2 in primary breast cancer. Br J Cancer. 1991 Mar;63(3):447-50. doi: 10.1038/bjc.1991.103.
PubMed 1672256Paterson MC, Dietrich KD, Danyluk J, Paterson AH, Lees AW, Jamil N, Hanson J, Jenkins H, Krause BE, McBlain WA, et al. Correlation between c-erbB-2 amplification and risk of recurrent disease in node-negative breast cancer. Cancer Res. 1991 Jan 15;51(2):556-67.
PubMed 1670762Brown RW, Allred CD, Clark GM, Osborne CK, Hilsenbeck SG. Prognostic value of Ki-67 compared to S-phase fraction in axillary node-negative breast cancer. Clin Cancer Res. 1996 Mar;2(3):585-92.
PubMed 9816207Thor AD, Liu S, Moore DH 2nd, Edgerton SM. Comparison of mitotic index, in vitro bromodeoxyuridine labeling, and MIB-1 assays to quantitate proliferation in breast cancer. J Clin Oncol. 1999 Feb;17(2):470-7. doi: 10.1200/JCO.1999.17.2.470.
PubMed 10080587Gyorffy B, Hatzis C, Sanft T, Hofstatter E, Aktas B, Pusztai L. Multigene prognostic tests in breast cancer: past, present, future. Breast Cancer Res. 2015 Jan 27;17(1):11. doi: 10.1186/s13058-015-0514-2.
PubMed 25848861Gupta S, Tran T, Luo W, Phung D, Kennedy RL, Broad A, Campbell D, Kipp D, Singh M, Khasraw M, Matheson L, Ashley DM, Venkatesh S. Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry. BMJ Open. 2014 Mar 17;4(3):e004007. doi: 10.1136/bmjopen-2013-004007.
PubMed 24643167Lundin M, Lundin J, Burke HB, Toikkanen S, Pylkkanen L, Joensuu H. Artificial neural networks applied to survival prediction in breast cancer. Oncology. 1999 Nov;57(4):281-6. doi: 10.1159/000012061.
PubMed 10575312Hajage D, de Rycke Y, Bollet M, Savignoni A, Caly M, Pierga JY, Horlings HM, Van de Vijver MJ, Vincent-Salomon A, Sigal-Zafrani B, Senechal C, Asselain B, Sastre X, Reyal F. External validation of Adjuvant! Online breast cancer prognosis tool. Prioritising recommendations for improvement. PLoS One. 2011;6(11):e27446. doi: 10.1371/journal.pone.0027446. Epub 2011 Nov 8.
PubMed 22087319Bhoo-Pathy N, Yip CH, Hartman M, Saxena N, Taib NA, Ho GF, Looi LM, Bulgiba AM, van der Graaf Y, Verkooijen HM. Adjuvant! Online is overoptimistic in predicting survival of Asian breast cancer patients. Eur J Cancer. 2012 May;48(7):982-9. doi: 10.1016/j.ejca.2012.01.034. Epub 2012 Feb 25.
PubMed 22366561Wishart GC, Azzato EM, Greenberg DC, Rashbass J, Kearins O, Lawrence G, Caldas C, Pharoah PD. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer. Breast Cancer Res. 2010;12(1):R1. doi: 10.1186/bcr2464. Epub 2010 Jan 6.
PubMed 20053270
Study at a glance
From the registry record, last updated by the sponsor on 20 Oct 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Correlation of Predictive Accuracy of PREDICT Version 2.2, (PREDICT V2.2) on a Retrospective Cohort of Indian Women With Operable Breast Cancer (OBC)
- ClinicalTrials.gov ID
- NCT04985253
- Acronym / sponsor ID
- PREDICT / 3055
- Conditions
- Operable Breast Neoplasms
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 2,780 participants (actual)
- Lead sponsor
- Tata Memorial CentreUniversity, hospital or other
- Study start
- 15 Nov 2018 (actual)
- Primary completion
- 18 Oct 2021 (actual)
- Study completion
- 31 Dec 2022 (estimated)
- First posted
- 2 Aug 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is an observational retrospective study which aims at comparing the 5-year survival estimates from "PREDICT V2.2" with observed 5-year outcome from our dataset of Indian women treated for operable breast cancer. "PREDICT V2.2" is a prognostication and treatment benefit tool developed in the UK. It is a tool available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions, for operable breast cancer patients. We hypothesize that 5-year overall survival (OS) predictions using "PREDICT V2.2" will have reasonable accuracy and applicability to the Indian operable breast cancer patients. The predictions, if accurate, will not only reassure the patients of the benefits of the treatment being offered, which outweigh the side effects but it will also make clinician as well as patient confident about avoiding potentially toxic systemic therapies, where the benefit is too small.
Detailed description
Adjuvant therapy for breast cancer is based on clinic-pathological prognostic and predictive markers.The most important prognostic marker is still presence of lymph node involvement1,2. Other factors that contribute to planning adjuvant systemic therapy include, tumor size3, grade3, hormone receptor status4, Her2/neu overexpression5-7, proliferation markers8-9, age at presentation, patient preferences, performance status and comorbidities. Accurate survival estimates, and the likely benefit of adjuvant therapy, are important aspects of information oncologists consider when making decisions following surgery for invasive, early breast cancer. Currently these decisions are based on known pathological prognostic factors including tumour size, tumour grade and lymph node status in addition to the relative risk reductions of any adjuvant therapy1-7.
The prognostic and predictive strengths of different factors are variable and the same factor can have different predictive or prognostic value according to the molecular subtype of breast cancer. These markers are not completely independent of each other10.
Several predictive models are now available to help estimate the survival and treatment benefits for individual patients.Multivariate Prediction Models (MPM) takes into consideration not just each marker but the effect with all possible combinations of these markers10. MPMs are of two types. They can either be multivariate prognostic model or a multigene predictive model. Examples10 of multivariate prognostic models are IHC4 assay, Adjuvant! Online and PREDICT. Multigene predictive models are OncotypeDx, MammaPrint, PAM50, EndoPredict.
Web based mathematical models which use algorithms to predict survival with or without systemic therapy after surgery, like 'Adjuvant! Online' and PREDICT V2.0 use patient characteristics to predict the survival with or without treatment. The inputs required are tumour size, number of nodes involved, grade of tumour, hormone receptor status, Her2 overexpression, Ki67 and comorbidities. Based on these inputs using an algorithm these tools calculate the overall survival at end of 5 and/or 10 years. Then they also predict what would be the added benefit of adjuvant systemic therapies singularly or with combinations.
However majority of these models that have been evaluated use the datasets of cancer registries in a particular geographical location or singles institute11,12. This makes blind application of these models to untested populations unpredictable. Various studies have tested web based prognostic models in different populations. In 2011 Hajage D, et al published their results regarding external validation of 'Adjuvant! Online',in a French and Dutch population13. The prediction was overall well-calibrated in the French data. But there was discordance in some subgroups of patients having high grade tumours and HER2 overexpression. Addition of HER2 status, Mitotic Index and Ki67 significantly improved the predictions. In the Dutch data set, the overall 10-year survival was overestimated by 'Adjuvant! Online', particularly in patients less than 40 years of age.Bhoopathyet al, in 2012 tested this tool in an Asian population and concluded that although it differentiates between good and bad prognosis, it systematically overestimates the survival and requires adaptation before usage in Asian population14.
Predict is an online prognostication and treatment benefit tool developed in the UK, using cancer registration and survival data recorded by the Eastern Cancer Registration and Information Centre (ECRIC) for 5694 women diagnosed in East Anglia from 1999-2003.15The model was validated in a second cohort of 5468 women from the West Midlands Cancer Intelligence Unit and is available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions. Wong et al, tested the predictive accuracy of PREDICT V1.0 in the southeast Asian population16. There were 67% Chinese patients while 13% were Indians. The median age in their study was 50 yrs. They showed concordance in observed and predicted OS in most subgroups except for women whore less than 40 years of age. After reviews in literature, for a better fit in various groups, PREDICT V1.0 was updated to version v2.0. V2.0 is equivalent to V1.0 but calibration of V2.0 has improved over V1.0 in patients diagnosed under the age of 40.17
Multigene predictive models like OncotypeDx, MammaPrint, PAM50, EndoPredict are restrictive in their use due to high cost, thus many oncologists in India use the freely available Web based mathematical models, like Adjuvant Online! or PREDICT V2.0. However, there is no data suggesting the validity of prediction using these models in Indian patients. Hence we propose a study to validate the tool within a trial setting, before advising its use in clinical practice.
With the aim to compare the 5-year survival estimates from Predict with observed 5-year outcome from the TMC dataset of Indian women treated for operable breast cancer.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Operable breast neoplasm cohort | – | Other: prediction of overall survival using Web based PREDICTV2.0 portalOperable breast cancer (OBC) ER +/Her2 neg or triple negative breast cancer patients diagnosed and treated at Tata Memorial Centre, Mumbai from 01 Jan 2010 to 31 Dec 2013 with a five-year follow up or events within the 5 years. |
Who may qualify
- Ages
- 18 to 99 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Participant data will be selected from all the patients underwent treatment for Breast neoplasm in Tata Memorial Hospital Mumbai-12 in year 2010-2013.
Key inclusion criteria (3 listed)
- OBC patients treated at TMH
- ER +/Her2 neg or TNBC
- We will include2780 women wherein events / 5-year follow up is available. We propose to have a blinded member of the DMG identify such cases and provide to the study team.
Key exclusion criteria (3 listed)
- . • Missing variables egpT size, chemotherapy details
- Lost to follow up
- Her2 overexpression positive or Equivocal on IHC. (This is being excluded to avoid the bias of incomplete treatment as a large number of patients treated in 2010-2013 may not have received Her2 targeted treatment in our setting)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| prediction of overall survival using Web based PREDICTV2.0 portalPredict is an online prognostication and treatment benefit tool developed in the UK, using cancer registration and survival data recorded by the Eastern Cancer Registration and Information Centre (ECRIC) for 5694 women diagnosed in East Anglia from 1999-2003. The model was validated in a second cohort of 5468 women from the West Midlands Cancer Intelligence Unit and is available online (www.predict.nhs.uk) providing 5-and 10-year survival estimates and treatment benefit predictions. Wong et al, tested the predictive accuracy of PREDICT V1.0 in the southeast Asian population. There were 67% Chinese patients while 13% were Indians. They showed concordance in observed and predicted OS in most subgroups except for women whore less than 40 years of age. | Other | Operable breast neoplasm cohort |
Primary outcome
Five year overall survival
Time frame: 5 years
To compare the observed 5 year overall survival of operable breast cancer patients with the one predicted by PREDICT V 2.2
1 secondary outcome
To compare the observed 5 year overall survival of operable breast cancer patients with the one predicted by PREDICT V2.0V 2.2 for subgroups like age at diagnosis, stage of disease, tumour grade and molecular class (ER/PR positive or TNBC)
Time frame: 5 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Oct 2022.
- Background: PubMed 2657970Saez RA, McGuire WL, Clark GM. Prognostic factors in breast cancer. Semin Surg Oncol. 1989;5(2):102-10. doi: 10.1002/ssu.2980050206.
- Background: PubMed 6352003Fisher B, Bauer M, Wickerham DL, Redmond CK, Fisher ER, Cruz AB, Foster R, Gardner B, Lerner H, Margolese R, et al. Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update. Cancer. 1983 Nov 1;52(9):1551-7. doi: 10.1002/1097-0142(19831101)52:93.0.co;2-3.
- Background: PubMed 6733019Koscielny S, Tubiana M, Le MG, Valleron AJ, Mouriesse H, Contesso G, Sarrazin D. Breast cancer: relationship between the size of the primary tumour and the probability of metastatic dissemination. Br J Cancer. 1984 Jun;49(6):709-15. doi: 10.1038/bjc.1984.112.
- Background: PubMed 10066085Hilsenbeck SG, Ravdin PM, de Moor CA, Chamness GC, Osborne CK, Clark GM. Time-dependence of hazard ratios for prognostic factors in primary breast cancer. Breast Cancer Res Treat. 1998;52(1-3):227-37. doi: 10.1023/a:1006133418245.
- Background: PubMed 1973070Borg A, Tandon AK, Sigurdsson H, Clark GM, Ferno M, Fuqua SA, Killander D, McGuire WL. HER-2/neu amplification predicts poor survival in node-positive breast cancer. Cancer Res. 1990 Jul 15;50(14):4332-7.
- Background: PubMed 1672256Winstanley J, Cooke T, Murray GD, Platt-Higgins A, George WD, Holt S, Myskov M, Spedding A, Barraclough BR, Rudland PS. The long term prognostic significance of c-erbB-2 in primary breast cancer. Br J Cancer. 1991 Mar;63(3):447-50. doi: 10.1038/bjc.1991.103.
- Background: PubMed 1670762Paterson MC, Dietrich KD, Danyluk J, Paterson AH, Lees AW, Jamil N, Hanson J, Jenkins H, Krause BE, McBlain WA, et al. Correlation between c-erbB-2 amplification and risk of recurrent disease in node-negative breast cancer. Cancer Res. 1991 Jan 15;51(2):556-67.
- Background: PubMed 9816207Brown RW, Allred CD, Clark GM, Osborne CK, Hilsenbeck SG. Prognostic value of Ki-67 compared to S-phase fraction in axillary node-negative breast cancer. Clin Cancer Res. 1996 Mar;2(3):585-92.
- Background: PubMed 10080587Thor AD, Liu S, Moore DH 2nd, Edgerton SM. Comparison of mitotic index, in vitro bromodeoxyuridine labeling, and MIB-1 assays to quantitate proliferation in breast cancer. J Clin Oncol. 1999 Feb;17(2):470-7. doi: 10.1200/JCO.1999.17.2.470.
- Background: PubMed 25848861Gyorffy B, Hatzis C, Sanft T, Hofstatter E, Aktas B, Pusztai L. Multigene prognostic tests in breast cancer: past, present, future. Breast Cancer Res. 2015 Jan 27;17(1):11. doi: 10.1186/s13058-015-0514-2.
- Background: PubMed 24643167Gupta S, Tran T, Luo W, Phung D, Kennedy RL, Broad A, Campbell D, Kipp D, Singh M, Khasraw M, Matheson L, Ashley DM, Venkatesh S. Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry. BMJ Open. 2014 Mar 17;4(3):e004007. doi: 10.1136/bmjopen-2013-004007.
- Background: PubMed 10575312Lundin M, Lundin J, Burke HB, Toikkanen S, Pylkkanen L, Joensuu H. Artificial neural networks applied to survival prediction in breast cancer. Oncology. 1999 Nov;57(4):281-6. doi: 10.1159/000012061.
- online predict toolLink provided by the sponsor.
- Individual participant dataSharing planned: No. To maintain the study participants data confidentiality and anonymity As per local regulations and Ethics committee mandate IPD will not be shared.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Nita S Nair, MCH principal investigator
Professor and Surgeon (Breast Oncology)
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Operable Breast Neoplasms, run by Tata Memorial Centre at 1 site in India.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 20 Oct 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in India. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Five year overall survival (time frame: 5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04985253, which also lists 17 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Oct 2022.