INTRODUCTION 37 ity; is it understood in biological terms how <strong>the</strong> exposure under study could produce <strong>the</strong> cancer <strong>of</strong> interest? However, while pertinent, <strong>the</strong> response to this question is not especially convincing one way or ano<strong>the</strong>r; it has proven all too easy to propose credible biological mechanisms relating most exposures to most cancers; and, on <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> failure to perceive such a mechanism may reflect only our ignorance <strong>of</strong> <strong>the</strong> state <strong>of</strong> nature. For <strong>the</strong> sake <strong>of</strong> completeness ano<strong>the</strong>r criterion <strong>of</strong> causality is mentioned: this relates to how <strong>the</strong> frequency <strong>of</strong> disease changes when <strong>the</strong> proposed cause is removed from (or added to) <strong>the</strong> environment. No doubt <strong>the</strong> response to manipulation <strong>of</strong> <strong>the</strong> exposure is <strong>the</strong> most cogent type <strong>of</strong> causal argument, but it does not concern <strong>the</strong> investigator dealing with <strong>the</strong> results <strong>of</strong> a particular <strong>case</strong>-<strong>control</strong> study. Finally, <strong>the</strong>re are two fur<strong>the</strong>r <strong>considerations</strong> to bear in mind when interpreting a result. First, as an alternative to <strong>the</strong> four interpretations discussed, it could be decided that a study is "unevaluable". This decision is usually arrived at by exclusion, that is, <strong>the</strong>re may be no basis <strong>for</strong> placing confidence in any <strong>of</strong> <strong>the</strong> o<strong>the</strong>r interpretations. The most frequent situation occurs when a study has no detectable flaw but its results are consistent with a chance effect. While <strong>the</strong> judgement <strong>of</strong> "unevaluable" may be tenable, it does not .mean that <strong>the</strong> study is in error or has no value. Unless <strong>the</strong> study is so small as to be hopelessly imprecise, it can still make a contribution, in <strong>the</strong> context <strong>of</strong> o<strong>the</strong>r studies, to evaluating <strong>the</strong> hypo<strong>the</strong>sis in question. Secondly, it is useful to keep in mind that <strong>the</strong> interpretation decided upon is not immutable. An investigator and <strong>the</strong> scientific community may favour one interpretation today and a different one later, in <strong>the</strong> light <strong>of</strong> knowledge acquired in <strong>the</strong> interim. REFERENCES Bailar, J.C. & Anthony, G.B. (1977) Most cited papers <strong>of</strong> <strong>the</strong> Journal <strong>of</strong> <strong>the</strong> National Cancer Institute 1962-75. J. natl Cancer Inst., 59, 709-714 Billewicz, W.Z. (1965) The efficiency <strong>of</strong> matched samples: an empirical investigation. Biometrics, 21,623-643 Boston Collaborative Drug Surveillance Program (1973) Oral contraceptives and venous thromboembolic disease, surgically confirmed gall-bladder disease, and breast tumours. Lancet, i, 1399-1404 Breslow, N. E. & Patton, J. (1979) Case-<strong>control</strong> <strong>analysis</strong> <strong>of</strong> cohort studies. In: Breslow, N. & Whittemore, A., eds, Energy and Health, Philadelphia, Society <strong>for</strong> Industrial and Applied Ma<strong>the</strong>matics, pp. 226-242 Clarke, E.A. & Anderson, T. W. (1979) Does screening by "Pap" smears help prevent cervical cancer? A <strong>case</strong>-<strong>control</strong> study. Lancet, ii, 1-4 Cole, P. (1973) A population-based study <strong>of</strong> bladder cancer. In: Doll, R. & Vodopija, I., eds, Host Environment Interactions in <strong>the</strong> Etiology <strong>of</strong> Cancer in Man, Lyon, International Agency <strong>for</strong> Research on Cancer (<strong>IARC</strong> Scientific Publications No. 7), pp. 83-87 Cole, P. (1979) The evolving <strong>case</strong>-<strong>control</strong> study. J. chron. Dis., 32, 15-27 Cole, P. & MacMahon, B. (1971) Attributable risk percent in <strong>case</strong>-<strong>control</strong> studies. Br. J. prev. soc. Med., 25, 242-244
38 COLE Cole, P., Elwood, J.M. & Kaplan, S.D. (1978) Incidence rates and risk factors <strong>of</strong> benign breast neoplasms. Am. J. Epidemiol., 108, 1 12-1 20 Cole, P., Hoover, R. & Friedell, G. H. (1972) Occupation and cancer <strong>of</strong> <strong>the</strong> lower urinary tract. Cancer, 29, 1250-1260 Cole, P., Mack, T., Rothman, K., Henderson, B. & Newell, G. (1973) Tonsillectomy and Hodgkin's disease (Letter to <strong>the</strong> Editor). New Engl. J. Med., 288, 634 Cole, P., Monson, R.R., Haning, H. & Friedell, G.H. (1971) Smoking and cancer <strong>of</strong> <strong>the</strong> lower urinary tract. New Engl. J. Med., 284, 129-134 Cornfield, J. (1951) A method <strong>of</strong> estimating comparative rates from clinical data. Application to cancer <strong>of</strong> <strong>the</strong> lung, breast and cervix. J. natl Cancer Inst., 11, 1269- 1275 Doll, R. & Hill, A.B. (1952) A study <strong>of</strong> <strong>the</strong> aetiology <strong>of</strong> carcinoma <strong>of</strong> <strong>the</strong> lung. Br. med. J., ii, 1271-1286 Edmondson, H.A., Henderson, B. & Benton, B. (1976) Liver-cell adenomas associated with use <strong>of</strong> oral contraceptives. New Engl. J. Med., 294, 470-472 Elwood, J.M., Cole, P., Rothman, K. J. & Kaplan, S.D. (1977) Epidemiology <strong>of</strong> endometrial cancer. J. natl Cancer lnst., 59, 1055-1060 Feinstein, A. R. (1979) Methodologic problems and standards in <strong>case</strong>-<strong>control</strong> research. J. chron. Dis., 32, 35-41 Gail, M., Williams, R., Byar, D.P. & Brown, C. (1976) How many <strong>control</strong>s? J. chron. Dis., 29, 723-731 Gordon, J., Reagan, J. W., Finkle, W. D. & Ziel, H. K. (1 977) Estrogen and endometrial carcinoma. An independent pathology review supporting original risk estimate. New Engl. J. Med., 297, 570-571 Greenberg, M. & Lloyd Davies, T.A. (1974) Meso<strong>the</strong>lioma Register 1967-68. Br. J. ind. Med., 31, 91-104 Gutensohn, N. & Cole, P. (1977) The epidemiology <strong>of</strong> Hodgkin's disease among <strong>the</strong> young. Int. J. Cancer, 19, 595-604 Gutensohn, N., Li, F., Johnson, R. & Cole, P. (1975) Hodgkin's disease, tonsillectomy and family size. New Engl. J. Med., 292, 22-25 Haenszel, W., Kurihara, M., Segi, M. & Lee, R.K.C. (1972) Stomach cancer among Japanese in Hawaii. J. natl Cancer lnst., 37, 969-988 Haenszel, W., Berg, J.W., Segi, M., Kurihara, M. & Locke, F.B. (1973) Large-bowel cancer in Hawaiian Japanese. J. natl Cancer Inst., 51, 1765-1779 Haenszel, W., Correa, P., Cuello, C., Guzman, N., Burbano, L.C., Lores, H. & Muiioz, J. (1976) Gastric cancer in Colombia. 11. Case-<strong>control</strong> epidemiologic study <strong>of</strong> precursor lesions. J. natl Cancer Inst., 57, 102 1-1 026 Halperin, M. (1977) Estimability and estimation in <strong>case</strong>-referent studies (Letter to <strong>the</strong> Editor). Am. J. Epidemiol., 105, 496-498 Herbst, A.I., Ulfelder, H. & Poskanzer, D.C. (1971) Adenocarcinoma <strong>of</strong> <strong>the</strong> vagina. Association <strong>of</strong> maternal stilbestrol <strong>the</strong>rapy with tumor appearance in young women. New Engl. J. Med., 284, 878-881 Horwitz, R. I. & Feinstein, A. R. (1 978) Alternative analytic methods <strong>for</strong> <strong>case</strong>-<strong>control</strong> studies <strong>of</strong> estrogens and endometrial cancer. New Engl. J. Med., 299, 1089-1094 Horwitz, R.I. & Feinstein, A.R. (1979) Methodologic standards and contradictory results in <strong>case</strong>-<strong>control</strong> research. Am. J. Med., 66, 556-564
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88 BRESLOW & DAY Fig. 3.1 Relative
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90 BRESLOW & DAY Considerations ext
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92 BRESLOW & DAY of this type can b
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94 BRESLOW & DAY decreases breast c
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96 BRESLOW & DAY E and those not ex
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98 BRESLOW & DAY The confounding ef
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104 BRESLOW & DAY there were limita
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106 BRESLOW & DAY to have a strong
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110 BRESLOW & DAY Table 3.6 Risk fo
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112 BRESLOW & DAY risk for some fac
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114 BRESLOW & DAY an additional cat
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116 BRESLOW & DAY Boice, J.D. & Mon
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118 BRESLOW & DAY Report of the Sur
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ANALYSIS OF GROUPED DATA Table 4.1
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ANALYSIS OF GROUPED DATA 125 such a
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Estimation of q ANALYSIS OF GROUPED
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ANALYSIS OF GROUPED DATA 129 for th
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ANALYSIS OF GROUPED DATA 131 analog
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ANALYSIS OF GROUPED DATA 133 Referr
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ANALYSIS OF GROUPED DATA 135 Halper
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ANALYSIS OF GROUPED DATA 137 are pa
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ANALYSIS OF GROUPED DATA 1.39 signi
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ANALYSIS OF GROUPED DATA 141 strata
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ANALYSIS OF GROLIPED DATA 143 appro
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ANALYSIS OF GROLIPED DATA 145 Table
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ANALYSIS OF GROUPED DATA 149 Nor wi
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ANALYSIS OF GROUPED DATA 151 Alcoho
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ANALYSIS OF GROUPED DATA 153 relati
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ANALYSIS OF GROUPED DATA 155 obtain
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ANALYSIS OF GROUPED DATA 157 Gart,
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ANALYSIS OF GROUPED DATA 159 Cov(x,
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CHAPTER V CLASSICAL METHODS OF ANAL
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164 BRESLOW & DAY 5.2 Matched pairs
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166 BRESLOW & DAY Approximate confi
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168 BRESLOW & DAY where 2.42 = F.,,
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170 BRESLOW & DAY The first and las
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ANALYSIS OF MATCHED DATA Case Expos
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176 BRESLOW & DAY or limits of 3.8-
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180 BRESLOW & DAY Case : control ra
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182 BRESLOW & DAY = 11.82, from whi
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184 BRESLOW & DAY observed and expe
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188 BRESLOW & DAY Miettinen, 0. S.
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LOGISTIC REGRESSION FOR LARGE STRAT
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LOGISTIC REGRESSION FOR LARGE STRAT
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LOGISPIC REGRESSION FOR LARGE STRAT
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LOGISTIC REGRESSION FOR LARGE STRAT
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6.8 Regression adjustment for confo
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6.9 Analysis of continuous data LOG
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7. CONDITIONAL LOGISTIC REGRESSION
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LOGIS-I-IC REGRESSION FOR MATCHED S
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Table 7.7 Matched multivariate anal
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LOGISTIC REGRESSION FOR MATCHED SET
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Table 7.9 (contd) C. Dose, duration
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LOGISTIC REGRESSION FOR MATCHED SET
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Table 7.12 Coefficients (f standard
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LOGISTIC REGRESSION FOR MATCHED SET
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LOGISTIC REGRESSION FOR MATCHED SET
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APPENDIX I AGE (YRS) ALCOHOL (GM/DA
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APPENDIX 11: GROUPED DATA FROM THE
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APPENDIX II YEAR OF DEATH AGE AT DE
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APPENDIX II YEAR OF DEATH AGE AT DE
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APPENDIX 111: MATCHED DATA FROM THE
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292 APPENDIX Ill CASE OR CONTROL AG
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294 APPENDIX Ill CASE OR CONTROL AG
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296 APPENDIX Ill CASE OR CONTROL CA
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APPENDIX IV MAIN PROGRAM .C MASTER
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300 APPENDIX IV 103 FORMAT(1H ,'NUM
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302 APPENDIX IV C UPON CONVERGENCE
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APPENDIX IV MODEL WITH 2 VARIABLES:
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APPENDIX IV MODEL WITH 4 VARIABLES:
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APPENDIX V MAIN PROGRAM DIMENSION N
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31 0 APPENDIX V C REFERENCES : C N.
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APPENDIX V CALL SYMINV~COVI,NP,COV,
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APPENDIX V SUBROUTINE SYMINVCA, N,
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APPENDIX V SUBROUTINE TWIDL(X, Y, Z
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APPENDIX V MODEL WITH SINGLE VARIAB
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APPENDIX V MODEL WITH 3 VARIABLES:
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APPENDIX VI LISTING OF PROGRAM LOGO
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C C C C C C APPENDIX VI SUBPROGRAM
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APPENDIX VI SUBROUTINE CALC(NTAB,P,
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328 APPENDIX VI SUBROUTINE MYSTCT,
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APPENDIX VI DOUBLE PRECISION FUNCTI
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332 APPENDIX VI C C C C C C REDUCE
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MODEL WITH LINEAR EFFECT OF YEAR RE
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TABLE A 0 E 31 12 10.64 32 4 5.12 3
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0 03 TABLE A B 0 E 0 E 9 1 6 7.06 6
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340 SUBJECT INDEX Biological monito
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342 SUBJECT INDEX Confounding risk
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344 SUBJECT INDEX Grouped data anal
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346 SUBJECT INDEX Matched case-cont
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348 SUB.IECT INDEX Poisson variabil
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350 SUB-IECT INDEX Tobacco consumpt