Skip to main content

Advertisement

Log in

Predicting Survival Outcome of Localized Melanoma: An Electronic Prediction Tool Based on the AJCC Melanoma Database

  • Melanomas
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

We sought to develop a reliable and reproducible statistical model to predict the survival outcome of patients with localized melanoma.

Methods

A total of 25,734 patients with localized melanoma from the 2008 American Joint Committee on Cancer (AJCC) Melanoma Database were used for the model development and validation. The predictive model was developed from the model development data set (n = 14,760) contributed by nine major institutions and study groups and was validated on an independent model validation data set (n = 10,974) consisting of patients from a separate melanoma center. Multivariate analyses based on the Cox model were performed for the model development, and the concordance correlation coefficients were calculated to assess the adequacy of the predictive model.

Results

Patient characteristics in both data sets were virtually identical, and tumor thickness was the single most important prognostic factor. Other key prognostic factors identified by stratified analyses included ulceration, lesion site, and patient age. Direct comparisons of the predicted 5- and 10-year survival rates calculated from the predictive model and the observed Kaplan-Meier 5- and 10-year survival rates estimated from the validation data set yielded high concordance correlation coefficients of 0.90 and 0.93, respectively. A Web-based electronic prediction tool was also developed (http://www.melanomaprognosis.org/).

Conclusions

This is the first predictive model for localized melanoma that was developed based on a very large data set and was successfully validated on an independent data set. The high concordance correlation coefficients demonstrated the accuracy of the predicted model. This predictive model provides a clinically useful tool for making treatment decisions, for assessing patient risk, and for planning and analyzing clinical trials.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Balch CM, Murad, TM, Soong SJ, Ingalls AL, Halpern NB, Maddox WA. A multifactorial analysis of melanoma: prognostic histopathological features comparing Clark’s and Breslow’s staging methods. Ann Surg. 1978;88:732–42.

    Article  Google Scholar 

  2. Eldh J, Boeryd B, Peterson LE. Prognostic factors in cutaneous malignant melanoma in stage I. A clinical, morphological and multivariate analysis. Scand J Plast Reconstr Surg. 1978;12:243–55.

    Article  CAS  PubMed  Google Scholar 

  3. Balch CM, Soong SJ, Murad TM, Ingalls AL, Maddox WA. A multifactorial analysis of melanoma. II. Prognostic factors in patients with stage I (localized) melanoma. Surgery. 1980;86:343–51.

    Google Scholar 

  4. Balch CM, Soong SJ, Murad TM, Ingalls AL, Maddox WA. A multifactorial analysis of melanoma. III. Prognostic factors in melanoma patients with lymph node metastases (stage II). Ann Surg. 1981;193:377–88.

    Article  CAS  PubMed  Google Scholar 

  5. Van Der Esch EP, Cascinelli N, Preda F, Morabito A., Bufalina R. Stage I melanoma of the skin: evaluation of prognosis according to histologic characteristics. Cancer. 1981;48:1668–73.

    Article  Google Scholar 

  6. Drzewiecki, KT, Andersen PK. Survival with malignant melanoma: a regression analysis of prognostic factors. Cancer. 1982;49:2414–9.

    Article  CAS  PubMed  Google Scholar 

  7. Balch CM, Soong SJ, Milton GW, et al. A comparison of prognostic factors and surgical results in 1,786 patients with localized (stage I) melanoma treated in Alabama, USA, and New South Wales, Australia. Ann Surg. 1982;196:677–84.

    Article  CAS  PubMed  Google Scholar 

  8. Balch CM, Soong SJ, Murad TM, Smith JW, Maddox WA, Durant JR. A multifactorial analysis of melanoma. IV. Prognostic factors in 200 melanoma patients with distant metastases (stage III). J Clin Oncol. 1983;1:126–34.

    CAS  PubMed  Google Scholar 

  9. Coit DG, Rogatko A., Brennan MF. Prognostic factors in patients with melanoma metastatic to axillary or inguinal lymph nodes. A multivariate analysis. Ann Surg. 1991;214:627–36.

    Article  CAS  PubMed  Google Scholar 

  10. Morton DL, Davtyan DG, Wanek LA, et al. Multivariate analysis of the relationship between survival and the microstage of primary melanoma by Clark level and Breslow thickness. Cancer. 1993;71:3737.

    Google Scholar 

  11. Buttner P, Garbe C, Bertz J, et al. Primary cutaneous melanoma Optimized cutoff points of tumor thickness and importance of Clark’s level for prognostic classification. Cancer. 1995;75:2499.

    Article  CAS  PubMed  Google Scholar 

  12. Balch CM, Soong SJ, Gershenwald JE, et al. Prognostic factors analysis of 17,600 melanoma patients: validation of the American Joint Committee on Cancer melanoma staging system. J Clin Oncol. 2001;19:3622–34.

    CAS  PubMed  Google Scholar 

  13. Gershenwald JE, Balch CM, Soong SJ, Thompson JF. Prognostic factors and natural history. In: Balch CM, Houghton AN, Sober AJ, Soong SJ, Atkins MB, Thompson JF, editors. Cutaneous melanoma. 5th ed. St Louis, MO: Quality Medical Publishing; 2009. p. 35–64.

  14. Balch CM, Milton GW, Shaw HM, Soong SJ, eitors. Cutaneous melanoma: clinical management and treatment results worldwide. Philadelphia: Lippincott; 1985.

    Google Scholar 

  15. Soong SJ. A computerized mathematical model and scoring system for predicting outcome in melanoma patients. In: Balch CM, Milton GW, editors. Cutaneous melanoma: clinical management and treatment results worldwide. Philadelphia: Lippincott; 1985. p. 353.

  16. Clark WH Jr, Elder DE, Guerry D, et al. Model predicting survival in stage I melanoma based upon tumor progression. J Natl Cancer Inst. 1989;81:1893–904.

    Article  PubMed  Google Scholar 

  17. MacKie RM, Aitchison T, Sirel JM, McLaren K, Watt DC. Prognostic models for subgroups of melanoma patients from the Scottish Melanoma Group database 1979–86, and their subsequent validation. Br J Cancer. 1995;71:173–6.

    CAS  PubMed  Google Scholar 

  18. Barnhill RL, Fine JA, Roush GC, Berwick M. Predicting five-year outcome for patients with cutaneous melanoma in a population-based study. Cancer. 1996;78:427–32.

    Article  CAS  PubMed  Google Scholar 

  19. Schuchter L, Schultz DJ, Synnestvedt M, Trock BJ, Guerry D, Elder DE, Elenitsas R, et al. A prognostic model for predicting 10-years survival in patients with primary melanoma. The Pigmented Lesion Group. Ann Intern Med. 1996;125:369–75.

    CAS  PubMed  Google Scholar 

  20. Sahin S, Rao B, Kopf AW, Lee E, Rigel DS, Nossa R, Rahman IJ, et al. Predicting ten-year survival of patients with primary cutaneous melanoma: a corroboration of a prognostic model. Cancer. 1997;80:1426–31.

    Article  CAS  PubMed  Google Scholar 

  21. Soong SJ, Zhang Y, Desmond R. Models for predicting outcome. In: Balch CM, Houghton AN, Sober A, Soong SJ, editors. Cutaneous melanoma. 4th ed. St. Louis: Quality Medical Publishing; 2003. p. 77–90.

  22. Soong SJ, Shaw HM, Balch CM, McCarthy WH, Urist MM, Lee JY. Predicting survival and recurrence in localized melanoma: a multivariate approach. World J Surg. 1992;16:191–5.

    Article  CAS  PubMed  Google Scholar 

  23. Balch CM, Buzaid AC, Soong SJ, Atkins MB, Cascinelli N, Coit DG, Fleming ID, et al. Final version of the American Joint Committee on Cancer staging system for cutaneous melanoma. J Clin Oncol. 2001;19:3635–48.

    CAS  PubMed  Google Scholar 

  24. Ding S, Soong SJ, Lin HY, Desmond R, Balch CM. Parametric modeling of localized melanoma prognosis and outcome. J Biopharm Stat. 2009;19:732–47.

    Article  PubMed  Google Scholar 

  25. Balch CM, Gershenwald JE, Soong SJ, Thompson JF, Atkins MB, Byrd DR, Buzaid AC, et al. Final version of 2009 AJCC melanoma staging and classification. J Clin Oncol. 2009;27(36):6199–206.

    Article  PubMed  Google Scholar 

  26. Cox DR. Regression models and life tables. J R Statist Soc. 1972;B34:187.

    Google Scholar 

Download references

Acknowledgment

The following institutions and study groups generously contributed their patients to the 2008 AJCC Melanoma Database (an asterisk indicates the institutions and study groups that contributed localized melanoma data for this study): *Sydney Melanoma Unit, Sydney, Australia (John F. Thompson, MD); Istituto Nazionale Tumori, Milan Italy (Natale Cascinelli, MD); San Pio X Hospital, Milan, Italy (Natale Cascinelli, MD); *Memorial Sloan-Kettering Cancer Center, New York, NY, Daniel G. Coit, MD); *The University of Texas M. D. Anderson Cancer Center, Houston, TX (Jeffrey E. Gershenwald, MD, Merrick I. Ross, MD, and Marcella Johnson); John Wayne Cancer Institute, Santa Monica, CA (Donald L. Morton, MD); Netherlands Cancer Institute, Amsterdam, The Netherlands (Omgo Niewig, MD); *University of Pennsylvania Hospital, Philadelphia, PA (Keith Flaherty, MD, and Phyllis A. Gimotty, PhD); *University of Michigan, Ann Arbor, MI (Timothy Johnson, MD); *H. Lee Moffitt Cancer Center, Tampa, FL (Vernon K. Sondak, MD, and Douglas S. Reintgen, MD); *University of Alabama at Birmingham, Birmingham, AL (Charles M. Balch, MD, Seng-jaw Soong, PhD, and Marshall Urist, MD); Eastern Cooperative Oncology Group (John M. Kirkwood, MD, and Michael B. Atkins, MD).; *Sunbelt Melanoma Trial Group (Kelly M. McMasters, MD); *Sentinel Lymph Node Working Group (Stanley Leong, MD); *Intergroup Melanoma Surgical Trial Group (Charles M. Balch, MD, and Seng-jaw Soong, PhD); National Cancer Institute, Naples, Italy (Corrado Caraco, PhD, MD). The planning and development of the AJCC staging system and predictive model has been guided by the AJCC Melanoma Task Force Committee consisting of the following members: Charles M. Balch, MD (chair), Jeffrey E. Gershenwald, MD (vice-chair), Seng-jaw Soong, PhD (vice-chair), Michael B. Atkins, MD, David R. Byrd, MD, Antonio C. Buzaid, MD, Natale Cascinelli, MD, Alistair J. Cochran, MD, Daniel G. Coit, MD, Alexander M. M. Eggermont, MD, David Frishberg, MD, Keith T. Flaherty, MD, Phyllis A. Gimotty, PhD, Allan C. Halpern, MD, Alan N. Houghton, Jr, MD, Marcella M. Johnson, MS, John M. Kirkwood, MD, Kelly M. McMasters, MD, Martin F. Mihm, Jr. MD, Donald L. Morton, MD, Merrick I. Ross, MD, Arthur J. Sober, MD, Vernon K. Sondak, MD, Kristen Stephens, CTR, John F. Thompson, MD. We thank Troy Bland, computer specialist, for programming the electronic prediction tool and for maintaining the Web site, and Connie Pitts for her assistance in manuscript preparation. Supported in part by a grant from the AJCC, by unrestricted grants from Schering Plough to the AJCC, and by research funds (including CA13148 from NCI) from the Comprehensive Cancer Center of the University of Alabama at Birmingham.

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to Seng-jaw Soong PhD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Soong, Sj., Ding, S., Coit, D. et al. Predicting Survival Outcome of Localized Melanoma: An Electronic Prediction Tool Based on the AJCC Melanoma Database. Ann Surg Oncol 17, 2006–2014 (2010). https://doi.org/10.1245/s10434-010-1050-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1245/s10434-010-1050-z

Keywords

Navigation